Patricia Esperanza Balderas-Cañas Gabriel de las Nieves Sánchez-Guerrero  Editors

Problem Solving In Operation Management

Problem Solving In Operation Management

Patricia Esperanza Balderas-Cañas Gabriel de las Nieves Sánchez-GuerreroEditors

Problem Solving In Operation Management

ISBN 978-3-030-50088-7 ISBN 978-3-030-50089-4 (eBook)https://doi.org/10.1007/978-3-030-50089-4

© Springer Nature Switzerland AG 2021This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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EditorsPatricia Esperanza Balderas-CañasFaculty of EngineeringNational Autonomous University of MexicoMexico City, Mexico

Gabriel de las Nieves Sánchez-GuerreroFaculty of EngineeringNational Autonomous University of MexicoMexico City, Mexico

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Prologue

Currently, Systems Thinking is a holistic, transdisciplinary, dynamic, and construc-tivist approach that allows explaining realities through their understanding and knowledge, considering the context and purpose of the systems that give it meaning, structures and functions that make it up, and processes, procedures, and actors that involved create a complex dynamic.

Since its inception, the metadiscipline of Systems Thinking has linked thought and action, and has traveled between the fields of scientific research and problem solving. It is through plural participation that its action is focused primarily on com-plex systems, either from the analysis of problematic situations, planning, design, optimization and even implementation.

The book shows a brief look at the potential of Systems Thinking in Problem Solving for intervention, management, and planning in organizations. It presents eight research works that are integrated in two parts: methodologies and techniques. The contributions with a methodological orientation are shown from the first to the fifth chapter of the book, and from the sixth to the eighth chapter, the contributions are directed towards the techniques.

It is increasingly common to find the use of Systems Thinking in the solution of problems of private, governmental, and social sector organizations. Systems Thinking is a conceptual framework that allows understanding reality and with it addressing the problems of organizations making use of mathematics, dynamic sys-tems, optimization methods, planning, economics, social sciences, and behavior sciences among others. It combines theory and practice, quantitative and qualitative aspects, both necessary and complementary worlds for the solution of problems.

The country needs to plan its future. The lack of planning in our country for solution of problems has led us to react more than to prevent or design our future. For this rea-son, faced with the complexity we find the problems once we have them, although we must accept that more and more we are looking for an objective image of the country we want. Perhaps if we had had this image in the past, we would not have lost half of our territory or we would not have made the same mistakes year after year. Although the General Law of Planning of the Republic has been enacted since 1930, it was not until 1980 that the first Global Development Plan 1980–1982 was drawn up. We can say that a culture of planning in the country is beginning to be developed.

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In order to act and transform reality, it is also necessary to have a set of methods and techniques for solving problems, and in this sense also in the country there has been a technical acculturation in the public, private, and social sectors. Mathematics is increasingly used. It is no longer seen as that cold, abstract part full of symbols. Today mathematics is immersed in planning, optimization methods, and simulation having an innumerable set of applications.

In tune with the above, the book is emblematic. In its first part, Chaps. 1, 2, 3, 4, and 5, it presents a series of chapters aimed at developing theoretical- methodological aspects. The second part, Chaps. 6, 7, and 8, focuses on the use and development of models at the technical level, which allow us to approach the knowledge of reality and the solution of specific problems.

In order to improve the functioning and management of the organizations, the book proposes in its first chapter the theoretical basis for the diagnosis of organiza-tions that is constructed from the point of view of the complexity sciences, the conceptual principles for the elaboration of a diagnosis and a procedure to carry it out, from the point of view of the sciences of complexity, and new social theories. A relevant stage in this procedure is the dynamic analysis of the organization. In this stage, various elements that define its complexity are identified, such as its attrac-tors, branches, chaotic states, strange attractors, situations on the edge of chaos, and its process or auto organization attempts, which can serve as the basis for building models of computational simulation.

Starting out with the theoretical support of systems thinking, the methodological basis of interactive planning and the necessary and complementary use of quantita-tive and qualitative techniques, the second chapter offers a participative process for building trend scenarios. Such process is comprised of five phases: (1) definition of the system and explanation of current situation, (2) forecasts integration, (3) incor-poration of the predictions, (4) future image creation, and (5) description of the connection between the visualized present and future. Using this process, the case study Valle de Toluca Aquifer Scenario by 2020 is presented.

Chapter 3 analyzes consultancy as a systemic intervention process. Three explana-tion lines are defined about the ineffectiveness of such activity: (a) the conditioning of consultancy to client’s preferences, (b) the conditioning of consultancy to the consul-tant’s practices and knowledge, and (c) the dominating factors in the consultancy sce-nario which may be certain techniques, practices, tools, methods, and methodologies at time of implementation. Furthermore, on the basis of Midgley’s systemic interven-tion notion, systemic theoretical methodological elements are identified and found in the consultancy process, which establish favorable conditions to the process.

The fourth chapter analyzes the innovation process, seeking to maintain or achieve a competitive advantage in the organization. The author establishes that the innovation process that occurs in organizations has no lineal pathway nor is mani-fested in quiet organizational conditions. It is postulated that three ruptures occur during the process: the rupture of use—associated to a need of the selected market, the technological rupture—associated to the technological requirements, and the economic rupture—associated to the viable strategic price. The process focuses on defining at least three technical objects to be assessed (which can be products, pro-cesses, procedures, services, or methods). The objects are evaluated using different tools, which value its potential in all three mentioned ruptures.

Prologue

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Part one of the book concludes with Chap. 5, to show the application of digraphs in the analysis of mathematical knowledge representation systems in the field of secondary education. The methodology is presented and discussed to analyze, under a systemic approach, the visual reasoning procedures that are given with the use of mathematical representations in the learning of differential calculus topics, in the upper intermediate level. The methodology helps in knowing how the one who learns acquires and utilizes some mathematical representation systems and how he/she organizes them to produce acceptable answers in the school setting. The sys-tems are modeled using digraphs, and through an experience with high school stu-dents, the robustness of the proposed methodology is shown.

In the second part of the book, the sixth chapter develops a modeling process which allows for park location out of the selection of green areas in an urban area. The pro-cess begins with the structuring of the problem and ends with the use of a procedure that interacts between a Geographical Information System (GIS) and a discrete loca-tion multi-objective optimization model. The incorporation of GIS facilitated the visual representation of map information as well as data that the zones have. Also, a study case carried out in Delegación Cuauhtémoc of Mexico City is described.

The seventh chapter proposes a model for locating bi-level services using a drug distribution network in the State of Mexico, which has been originally presented as one with a sole objective. The strategy to solve multi-objective problems has been useful in situations where there is more than one objective, which in many cases may contradict themselves, but this approach does not consider the possible inter- dependency among them, a condition that takes multilevel programming into account. The proposed model was applied to a distribution of medication networks in the State of Mexico, for which it offers the best locations for warehouses.

Finally, the book concludes with the eighth chapter that offers an alternative for the determination of the demand in the control of inventories using fuzzy sets. It deals with the need that many Mexican enterprises have of having an alternative to determine the demand in inventory control, such being considered an additional or unnecessary cost, it’s carried out with the basis of experience and subjective judg-ments by the administration. To take advantage of this need, the use of fuzzy sets was used to determine the demand and its behavior in inventories control for the MRP models and EOQ. Considering the demand as a fuzzy number, its calculation is executed under uncertainty conditions, and in this way, it incorporates the subjec-tive knowledge and the administrative experience for its determination.

Finally, the thought of systems in the solution of problems, from the methods and techniques of optimization, planning, and simulation, will have an increasing devel-opment in the measure that they are directed to obtain the best possible result, and in this way raise the quality of life of society. These tools will be very powerful in the twenty-first century, and this book shows it.

Mexico City, Mexico Manuel Ordorica Mellado Patricia Esperanza Balderas-Cañas Gabriel de las Nieves Sánchez-Guerrero

Prologue

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BUILDINGTREND

SCENARIOS

CONSULTINGCHAP 3

INTERVENTION

SCHOOLLEARNING

BI-LEVELPROGRAMMING

CHAP 7

PROBLEMSOLVING

THINKING OF APPLIEDSYSTEMS

ORGANIZATIONS PLANNING

MANAGEMENT

DIAGNOSIS

COMPLEXITY

DYNAMICS

DIFFERENTIATION

INNOVATIONPROCESS

CHAP 4

MULTI-CRITERIALOCATION

MODELINGPROCESS

LOCALIZATION

RUPTURES

FUZZYOPTIMIZA

FUZZYOPTIMIZATION

MRPFUZZY

EOQFUZZY

INVENTORYAND FUZZY

DEMAND

NETWORKS

DISTRIBUTION

VISUALTHINKING

MATHREPRESENTATIONS

Consultingprocess

mentalframework

WATERSCENARIO

Structure of Part I

Prologue

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Introduction

This book is about problem solving in management of systems engineering cases. The content is presented in two parts, one for methodologies and the second for techniques. In the first chapter, a methodology for the diagnosis of the organization dynamics is discussed from the point of view of the Complexity Approach in order to improve and solve problems related with its operation and management.

The author of the second chapter reasons about a process for building trend in planning scenarios for problem solving in public and private organizations by five phases: (1) system definition and explanation of the current situation, (2) integration of forecasts, (3) integration of the predictions, (4) the construction of the future image, and (5) a description of the connection between the present and the future.

The third chapter is dedicated to explaining the organizational consulting inef-fectiveness where three reasons are presented. Two of those reasons are associated to the actors involved in the consulting process; the third reason is associated to the intervention process in problem solving.

In the fourth chapter, the objective of the author is identify the technological, economic, and usage ruptures, for the purpose of showing their importance in the stabilization of a process, aimed at reaching a transformation, named the innovation process. In problem solving, the innovation will be considered as “the introduction of a new or significantly improved product or process of a new marketing or organi-zational method in the company’s internal practices or external relations.”

The author of the fifth chapter presents and discusses a methodology to analyze, under a systemic approach, the visual reasoning processes given with the use of mathematical representations when learning Differential Calculus at a high school level. Her interest knows how those who learn, acquire, and use some of the systems of mathematical representation organize them to produce acceptable responses in the school environment.

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Contents

Part I Methodologies

1 Theoretical-Methodological Basis for Complex Organization Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . 3Felipe de Jesús Lara-Rosano 1.1 The Dynamic Diagnostic of a Complex Organization . . . . . . . . . . . 3 1.2 Organizations as a Complex System . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Analysis of Complex Organization . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.3.1 Analysis of Complex Organization Dynamics . . . . . . . . . . . 6 1.4 Diagnostic of Complex Organizational Dynamics . . . . . . . . . . . . . 11 1.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15References and Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2 Methodology for Building Trend Scenarios . . . . . . . . . . . . . . . . . . . . . 17Gabriel de las Nieves Sánchez-Guerrero 2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2.1.1 Scenarios in Interactive Planning . . . . . . . . . . . . . . . . . . . . . 18 2.1.2 Trend Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.2 Proposed Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.2.1 System Analysis and Current Situation Explanation . . . . . . 27 2.2.2 Forecasts Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.2.3 Predictions Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.2.4 Construction of Future Image . . . . . . . . . . . . . . . . . . . . . . . 29 2.2.5 Connection Between Present and Future:

Scenario Writing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

3 Consulting as a Systemic Intervention Process . . . . . . . . . . . . . . . . . . 47Benito Sánchez-Lara and Oscar Everardo Flores-Choperena 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3.2 Consultancy Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

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3.3 Consulting Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.3.1 Kubr’s Consulting Process . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.3.2 Morfín’s Consulting Process . . . . . . . . . . . . . . . . . . . . . . . . 51 3.3.3 Block’s Consulting Process . . . . . . . . . . . . . . . . . . . . . . . . . 52 3.3.4 Systems Method of Ochoa-Rosso . . . . . . . . . . . . . . . . . . . . 52 3.3.5 Summarizing the Consulting Processes . . . . . . . . . . . . . . . . 53

3.4 Systemic Intervention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 3.4.1 Consultancy as a Systemic Intervention . . . . . . . . . . . . . . . 54 3.4.2 Critical Thinking in Consultancy . . . . . . . . . . . . . . . . . . . . . 55 3.4.3 Systemic Intervention Conditions

in Consulting Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

4 The Role of Technological, Economic, and Usage Ruptures in the Innovation Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65Cozumel A. Monroy-León 4.1 The Context of Innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 4.2 Problem to Be Addressed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.3 Innovative Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

5 Digraphs in the Analysis of Systems’ Representation of Mathematical Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81Patricia Esperanza Balderas-Cañas 5.1 Representation of Mathematical Knowledge . . . . . . . . . . . . . . . . . . 81 5.2 Visual Reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 5.3 Representation Systems of Mathematical Knowledge

and Visual Reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 5.3.1 Visual Reasoning and Visualization . . . . . . . . . . . . . . . . . . . 86

5.4 Analysis of Systems of Representation of Math Knowledge . . . . . 89 5.4.1 Categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

5.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 5.5.1 Pedagogic Implications and Recommendations . . . . . . . . . 96

Annex 1: Extract of the Teaching Guide . . . . . . . . . . . . . . . . . . . . . . . . . 97Path of Water Flow Coming Out from a Hose . . . . . . . . . . . . . . . . . . 97

Annex 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98References and Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

Part II Techniques

6 Decision-Making with Multicriteria Optimization and GIS for Park Locations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105Mayra Elizondo-Cortés and Adela Jiménez-Montero 6.1 The Problem of Park Locations in Mexico City . . . . . . . . . . . . . . . 105

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6.2 Modeling Process for Park Locations . . . . . . . . . . . . . . . . . . . . . . . 106 6.3 Structuring the Problem of Park Location

and Mathematic Modeling Methodology . . . . . . . . . . . . . . . . . . . . . 107 6.4 Application for Delegación Cuauthémoc in Mexico City . . . . . . . . 112 6.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

7 A Service Location Model in a Bi-level Structure . . . . . . . . . . . . . . . . 117Zaida E. Alarcón-Bernal and Ricardo Aceves-García 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 7.2 Bi-level Programming Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 7.3 Model Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119

7.3.1 P-Median Location Model . . . . . . . . . . . . . . . . . . . . . . . . . . 119 7.3.2 General Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 7.3.3 Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 7.3.4 Bi-level Programming Problems . . . . . . . . . . . . . . . . . . . . . 121 7.3.5 Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 7.3.6 Discrete Bi-level Problem . . . . . . . . . . . . . . . . . . . . . . . . . . 122

7.4 Formulation of Bi-level Search Services Model . . . . . . . . . . . . . . . 123 7.4.1 General Model, Problem (4) . . . . . . . . . . . . . . . . . . . . . . . . 123 7.4.2 Solution Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 7.4.3 Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

7.5 Model Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 7.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131References and Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132

8 Determining the Demand in Inventory Policies for Mexican Companies Using Fuzzy Sets . . . . . . . . . . . . . . . . . . . . . . 135Ricardo Aceves-García and Zaida E. Alarcón-Bernal 8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135

8.1.1 Techniques Known and Used for Controlling Inventories in Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136

8.1.2 Data from Inventory Records, Problems with Uncertainty and EOQ and MRP Models . . . . . . . . . . . 137

8.2 Economic Order Quantity (EOQ) Model with Fuzzy Demand, Without Production or Deficit . . . . . . . . . . . . 139 8.2.1 Analysis of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146

8.3 MRP Model Considering the Demand of a Fuzzy Number . . . . . . . 147 8.3.1 Demand as a Fuzzy Number . . . . . . . . . . . . . . . . . . . . . . . . 154

8.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

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About the Authors

Ricardo  Aceves-García studied Chemical Engineering at the Autonomous University of Puebla, Mexico, and obtained a master’s in sciences and a PhD in Operational Research from the National Autonomous University of Mexico (UNAM). He has been working in various projects in the field of Transportation, Operational Research, and Optimization for both public and private organizations. At present, he is a Full-Time Professor and Researcher at the Engineering Graduated School of the UNAM, and his main lines of research are process optimization, net-work transportation, location services, and services operations.

Zaida E. Alarcón-Bernal obtained a doctoral degree in Engineering in the area of operations research, a master’s degree in Engineering (Hons.), and a degree in Actuarial Science, all from the National Autonomous University of Mexico. She is a Full-Time Professor at the Engineering Faculty of the UNAM in the Biomedical Systems Engineering Department. She belongs to the research group on Optimization in Service Companies in the Systems Engineering Department of the Engineering Faculty at the UNAM. She has participated in several consulting projects in public and private institutions. Her lines of research include hospital logistics, bi-level pro-gramming, and stochastic programming.

Patricia Esperanza Balderas-Cañas holds a PhD (Hons.) in Pedagogy, a master’s degree in Mathematics Education, and a degree in Mathematics, all of them from UNAM.  She is Full-Time and Definitive Professor in the Systems Engineering Department, UNAM-FI. Her research lines are on operations research (inventory theory, combinatorial optimization, and systems modeling) and structural model for learning research.

Felipe de Jesús Lara-Rosano holds a Doctoral degree in Systems Engineering from the National Autonomous University of Mexico (UNAM). He was Senior Researcher in the Institute for Applied Sciences and Technology, where he coordi-nated the Group of Cybernetics and Complex Systems and now coordinates the Academic Program of Social Complexity at the Center for Complexity Sciences of

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the UNAM. He is Life Senior Member of the IEEE and his current interests are around the analysis, modeling, and simulation of complex social systems.

Mayra  Elizondo-Cortés has a Doctoral and Master’s degrees in Operations Research from the School of Engineering of the UNAM and a degree in Applied Mathematics and Computation. She is a Full-Time Professor in the Systems Engineering Department, UNAM- FI. Her main lines of research are optimization, simulation, and multicriteria analysis applied essentially to logistics and supply chain processes. She has published notes on Computational Complexity and Simulation and articles in the Journal of Applied Research and Technology, International Journal of Automotive and Mechanical Engineering, and Journal of Engineering Research and Technology.

Oscar Everardo Flores-Choperena has a master’s degree in Engineering from UNAM, also studied Industrial and Systems Engineering at UNITEC. He partici-pated in the TREPCAMP Entrepreneurship Advanced Program at UC Berkeley. Nowadays he is pursuing master´s degree in Technology Management at UNAM. He has been a business consultant for based technology enterprises, he applied lean methodologies for rapid business model validation, and supports the creation of 10 startups; he has applied consulting as a systemic intervention process for the univer-sity’s high- technology business incubator at the National Autonomous University of Mexico.

Adela Jiménez-Montero has a degree in Applied Mathematics and Computation and a master’s degree in Operations Research from the School of Engineering at UNAM. She has 9 years of experience in risk for the financial sector, having worked with two of the largest banking institutions in Mexico. Her professional career began in BBVA, working as a risk adviser for RBB and mortgages products. She is currently working for HSBC as Risk Manager of retail customers and has collabo-rated in the process of defining original strategies for credit cards and customer view analysis, topics related to the pre-approval process of credits, costs and processes optimization, customer's segmentation, fraud monitoring and control, income infer-ence, development of growth strategies, and risk control, taking care of both cus-tomer and bank benefits.

Cozumel A. Monroy-León obtained her PhD in Industrial Engineering from the National Polytechnic Institute of Grenoble, France. For 2 years she worked in the Health Policy Coordination of the Medical Benefits Directorate of the IMSS, designing projects that improve the quality of care of the beneficiaries. From 2006 to 2017, she was a subject Professor at the UNAM Engineering graduate where she taught courses on Technological Innovation, Technology Management, Organizational Change Management, and Technological Development for New Products.

About the Authors

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Manuel Ordorica-Mellado is an actuary, demographer specialized in mathemati-cal demography, a doctor of Operations Research, and a Mexican academic from El Colegio de México (COLMEX). He was President of the Mexican Demographic Society. He studied the actuary career at the Faculty of Sciences of the National Autonomous University of Mexico (UNAM). Later, he obtained the demography master's degree from COLMEX. He obtained his doctorate with an honorable men-tion in Engineering with a specialty in Operations Research at UNAM, with his doctorate thesis “The Kalman Filter in Population Planning.” He was Head of the Department of Demographic Evaluation and Analysis in the General Directorate of Statistics at the National Institute of Statistics, Geography and Informatics (INEGI). From 1977 to 1987, he was Director of Population Studies of the National Population Council (CONAPO), as well as consultant in population education for the United Nations Educational, Scientific and Cultural Organization (UNESCO). In the area of teaching and academia, he is Professor-Researcher in Demography and the Doctorate in Population Studies at COLMEX.  He is a Member of the Editorial Board of Population magazine (INED, Paris).

Manuel Ordorica es actuario, demógrafo especializado en demografía matemática, doctor en investigación de operaciones y académico mexicano de El Colegio de México. Fue presidente de la Sociedad Mexicana de Demografía. Estudió la carrera de actuario en la Facultad de Ciencias de la Universidad Nacional Autónoma de México. Posteriormente cursó la maestría de Demografía por El Colegio de México; se doctoró con mención honorífica en Ingeniería con especiali-dad en Investigación de Operaciones en la UNAM, con su tesis de doctorado El filtro de Kalman en la planeación demográfica. Fue jefe del departamento de evalu-ación y análisis demográfico en la Dirección General de Estadística en el Instituto Nacional de Estadística Geografía e Informática (INEGI). De 1977 a 1987 fue director de Estudios de Población del Consejo Nacional de Población (CONAPO), así como consultor en educación en población de la Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura (UNESCO). En el área de docen-cia y de la academia es coordinador de la Maestría en Demografía y del Doctorado en Estudios de Población en COLMEX. Fungió como director del Centro de Estudios Demográficos y de Desarrollo Urbano de El Colegio de México. Forma parte del Consejo Editorial de la revista Population (INED, París).

Gabriel  de  las  Nieves  Sánchez-Guerrero holds a Doctoral degree (Hons.) in Systems Engineering from the Engineering Graduate School at UNAM. Nowadays he is Full-Time and Definitive Professor in the Systems Engineering Department of the Faculty of Engineering (UNAM-FI). His research interests include the heuristic techniques for participatory planning and systems interactive evaluation. His cur-rent research is heuristic systemic evaluation.

Benito Sánchez-Lara holds a Doctoral and master’s degrees in the Engineering Program from the UNAM and the bachelor’s degree in chemical engineering. Nowadays is Full-Time Professor in the Systems Engineering Department of the UNAM-FI, where is involved in Organizational and Transportation Systems Planning. His research interests include logistics and supply chain, tactical plan-ning, resilience, and viable systems analysis.

About the Authors

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Contributors

Ricardo Aceves-García Department of Systems, Faculty of Engineering, National Autonomous University of Mexico, Mexico City, Mexico

Zaida  E.  Alarcón-Bernal Department of Biomedical Systems Engineering, Faculty of Engineering, National Autonomous University of Mexico, Mexico City, Mexico

Patricia  Esperanza  Balderas-Cañas Department of Systems, Faculty of Engineering, National Autonomous University of Mexico, Mexico City, Mexico

Felipe de Jesús Lara-Rosano Complexity Sciences Center, National Autonomous University of Mexico, Mexico City, Mexico

Mayra Elizondo-Cortés Department of Systems, Faculty of Engineering, National Autonomous University of Mexico, Mexico City, Mexico

Oscar  Everardo  Flores-Choperena Materials Research Institute, National Autonomous University of Mexico, Chalco, Mexican State, Mexico

Adela  Jiménez-Montero Department of Systems, Faculty of Engineering, National Autonomous University of Mexico, Mexico City, Mexico

Cozumel  A.  Monroy-León Department of Systems, Faculty of Engineering, National Autonomous University of Mexico, Mexico City, Mexico

Gabriel  de  las  Nieves  Sánchez-Guerrero Department of Systems, Faculty of Engineering, National Autonomous, University of Mexico, Mexico City, Mexico

Benito Sánchez-Lara Department of Systems, Faculty of Engineering, National Autonomous University of Mexico, Mexico City, Mexico

Introduction

This book is about problem-solving in management of systems engineering cases. The content is presented in two parts, one for methodologies and the second for techniques. In the first chapter, a methodology for the diagnosis of the organization dynamics is discussed from the point of view of the complexity approach in order to improve and solve problems related to its operation and management.

The author of the second chapter reasons about a process for building trend in planning scenarios for problem-solving in public and private organizations by five phases: (1) system definition and explanation of the current situation, (2) integration of forecasts, (3) integration of the predictions, (4) the construction of the future image, and (5) a description of the connection between the present and the future.

The third chapter is dedicated to explaining the organizational consulting inef-fectiveness where three reasons are presented. Two of those reasons are associated with the actors involved in the consulting process; the third reason is associated with the intervention process in problem-solving.

In the fourth chapter, the objective of the author is to identify the technological, economic, and usage ruptures, for the purpose of showing their importance in the stabilization of a process, aimed at reaching a transformation, named the innovation process. In problem-solving, the innovation will be considered as “the introduction of a new or significantly improved product or process, of a new marketing or orga-nizational method in the company’s internal practices or external relations.”

The author of the fifth chapter presents and discusses a methodology to analyze, under a systemic approach, the visual reasoning processes given with the use of mathematical representations when learning differential calculus, at a high school level. The interest of the research focuses on recognizing how the students acquire and use some systems of mathematical representation and how they organize them to produce acceptable answers in the school environment.

Part IMethodologies

3© Springer Nature Switzerland AG 2021P. E. Balderas-Cañas, G. de las N. Sánchez-Guerrero (eds.), Problem Solving In Operation Management, https://doi.org/10.1007/978-3-030-50089-4_1

Chapter 1Theoretical-Methodological Basis for Complex Organization Diagnosis

Felipe de Jesús Lara-Rosano

1.1 The Dynamic Diagnostic of a Complex Organization

In the present context of rapid change and turbulence, it is needed to transform the organizations to give them greater viability, adaptability, efficiency, and dynamism (McMillan 2008).

This implies a challenge that is neither a minor nor cosmetic: it is necessary to develop new strategies and methods to improve organizations. This leads to the design of new management practices and the development of different forms of interaction between the organizational system elements (Stacey 2001) and formu-lates operational processes more flexible and suitable to this circumstance while attaining standards of quality and excellence.

To do this, it has been taken into account that from the 1980s onward, a new sci-ence approach was developed, which has revolutionized physics, chemistry, and biology (Nicolis and Prigogine 1994). It is the complex systems approach, which comprises, among others, the self-organized systems theory (Holland 1995), the complex adaptive systems theory, the dynamics of social networks theory (Newman et al. 2006), chaos theory (Eve 1997), and fractal geometry (Mandelbrot 1987).

In the social sciences, innovative approaches to social theory have appeared also, based on the interaction of individual agents (Epstein 2006; Epstein and Axtell 1996), self-organization, and social emergency (Sawyer 2005). Among these approaches, the ones that stand out are social constructivism (Giddens 1991, 1998), symbolic interactionism (Blumer 1969; Hewitt 1976), complex responsive pro-cesses in organizations (Stacey 2001), society and social systems theory (Luhmann 1984), sociocybernetics (Geyer and van der Zouwen 1992; Lara-Rosano 2002), computational sociology (Gilbert 2008), sociomatics (Castañeda 2009), sociophys-ics (Galam 2012), and communities of practice (Wenger 1998).

F. de Jesús Lara-Rosano (*) Complexity Sciences Center, National Autonomous University of Mexico, Mexico City, Mexico