Hierarchical Multiplex Structured Model for Vehicle Routing,
Scheduling, and Dispatching Problems Tokyo Institute of Technology
Kewei Chen, Kaoru Hirota 2002 Slide 2 Distribution System: (
Delivery Problem) [more than 30 years] ( Dispatching Problem)
Vehicle Routing Problem [Taillard 97, Potvin 96, ] Vehicle
Scheduling Problem [Igarashi 95, Bagchi 91, ] Vehicle Dispatching
Problem [Benyahia 98, Leclerc 97, ] Real World Problem Conventional
Approaches Complex Variety Real World Problem Mixture Flexible
Consignor Transporter Consignee Profit Share ComputingMethod
Efficiency High Speed PracticeFlexibility Slide 3 What is the
VRSDP/SD Problem Depot User(1) User(..) User(n) User(..) User(N)
Orders Vehicle(1) Vehicle(L) Cost Earnings Services Schedule
Shortest Route Assignment Slide 4 Y1Y1 UnUn V1V1 V Depot Order
Vehicle User Knowledge Base Initial Input Information OmOm N M R L
R Q D D Trip Tour UNUN OMOM YRYR O1O1 O2O2 U1U1 U2U2 U3U3 U2U2 U4U4
O 101 O 102 O 103 UnUn OmOm YrYr V New Concept of the VRSDP/SD
Problem X1X1 X2X2 XqXq XqXq YrYr XQXQ VLVL Slide 5 Vehicle Working
Service Appointed Time Service Evaluation Functions Total Working
Cost Average Loading Capacity Working Balance Working Capacity
Slide 6 Atomic Layer Fluctuation area of System cost Molecular
Layer Forming area of System state Individual Layer Decision area
of System plan Atomic Layer Fluctuation area of System cost
Molecular Layer Forming area of System state Individual Layer
Decision area of System plan Order Order TripTrip Trip TripTrip
Trip Trip Hierarchical Multiplex Structure Model OrderOrderOrder
OrderOrder TourTourTourTour Slide 7 Using Object-oriented Paradigm
HIMS Structure - (Using Object-oriented Paradigm) Atomic Layer
Molecular Layer Individual Layer Order User Object Trip Object Tour
Object Depot Object Initialization Base Object Tabu Search
Simulated Annealing Tabu Search Global Search Fuzzy Inference
Vehicle Object Order(1) Order(m) Order(M) Trip(1) Trip(q) Trip(Q)
Tour(1) Tour(r) Tour(R) r1r2 R1R2 11 1112 Q1 q2 Vehicle(L) Vehicle
( ) Vehicle(1) q1 Slide 8 Experiment 1 Working with All Vehicles
ITEM Working Cost (hour) Loading Rate (%) Working Balance (min)
Working Capacity (unit) Service 1 (time) (%) Service 2 (work) (%)
HIMS927.390.158.6090.288.3 Expert981.786.673.2081.880.6 Experiments
2 Working with Fewer Vehicles ITEM Working Cost (hour) Loading Rate
(%) Working Balance (min) Working Capacity (unit) Service 1 (time)
(%) Service 2 (work) (%) HIMS874.191.352.3886.780.2
Expert943.685.768.2582.473.6 (1 Depot, 95 Vehicles) VRSDP/SD
Problem for Tank Lorry Slide 9 Y1Y1 UnUn V1V1 V Depot Order Vehicle
User Knowledge Base Initial Input Information OmOm N M R L R Q D1D1
DpDp Trip Tour O1O1 U1U1 YRYR New Concept of the VRSDP/MD Problem
DpDp DPDP VLVL O2O2 U2U2 O 21 O 22 O 23 U3U3 U2U2 U4U4 UNUN OMOM
U5U5 O 66 U8U8 O 68 U9U9 YrYr XqXq YrYr X1X1 X2X2 XqXq X.. XQXQ V
constants variables conditions O 78 Slide 10 Extended HIerarchical
Multiplex Structure (HIMS ) V1V1 D1pD1p D.. R J.... D1PD1P V D p
D.. R J.... D.. L D p J.... VLVL DLpDLp D.. R J.... DLpDLp Atomic
Level Molecular Level Individual Level Working Balance Loading
Capacity Running Cost Arrival Time Aims Molecular Level: Aims .
Trip Move (between tours) . Trip Exchange (between tours) . Trip
Order Optimize (inside tour) . Depot Exchange (inside tour) Methods
Methods Tabu Search ( , , ), Global Search ( ) Slide 11 Using
Object-oriented Paradigm HIMS + Model -- (Using Object-oriented
Paradigm) O1O1 O2O2 O M-1 OMOM X1X1 O 11 O 12 X2X2 O 21 XqXq O q1 O
q3 X Q-1 O Q-11 O Q-12 XQXQ O Q1 O q2 OmOm Y1Y1 X 11 Y2Y2 X 21 YrYr
X r1 X r2 Y R-1 X R -1 1 YRYR X R1 X 22 AtomicMolecular Individual
Order/User ObjectTrip ObjectTour Object Depot ObjectInitialize/Base
Object Tabu Search / Simulated annealingTabu Search / Global Search
Fuzzy Inference Vehicle Object X R1 V1V1 V2V2 V V L-1 VLVL D1D1
D2D2 DpDp D P-1 DPDP Slide 12 date#O m TCTCC BCBC VCVC STST SVSV
Best 12/0940960890.5688.44095.3795.2786 th
12/11481068192.3855.21091.4596.93128 th
12/1442967494.0272.10091.8795.92136 th Experiment Working with all
Vehicles date#O m TCTCC BCBC VCVC STST SVSV Best
12/0940958791.9653.72692.3787.98167 th
12/11481002491.6149.78694.0884.17184 th
12/1442891094.6757.73892.8584.1385 th Experiment Working with
minimum Vehicles Real World Data Delivery Area Tokyo Data Used for
3 days No. of Depots 3 Vehicles Available 24 Slide 13 Dispatching
Combining Sales and Delivery Business Slide 14 HIMS Computational
Model V1V1V1V1 SD 1 p D.. R J.... D1PD1PD1PD1P V SD p D.. R J....
D.. L D p J.... VLVLVLVL SD L p D.. R J.... DLpDLpDLpDLp Atomic
Level Molecular Level Individual Level Middle Depot Change Middle
Depot Change (inside tour) Initial Depot Change Initial Depot
Change (inside tour) Operations Molecular Level Operations Slide 15
date#O m T cost C cost B cost V cost STST SVSV Best
11/0230935990.165.8894.992.6184 th 11/06381049191.452.9691.492.9102
th 11/0834905992.756.6894.194.771 th Operator T cost C cost B cost
V cost STST SVSV HIMS ++ (20 min) Better 90% 66 min Better 90%
Better Experts (0.5 day) Good 83% 90 min Good 80% Good Comparison
about Experimental results Experiment Dispatching with Least
Vehicles Slide 16 Effects of Butsuryu-kun Daily Business Views
Decreasing Planning Time Decreasing Used Vehicles Keeping Delivery
Conditions Standardization of Works Efficiency of Jobs Middle/Long
Range Strategies Physical Distribution Footholds Depot Locations
Setting Transit Footholds & delivery Areas Cooperative
Deliveries Vehicle Numbers & Types Skilled Knowledge
Flexibility & Extensibility Slide 17 HIMS, HIMS+, HIMS++ Models
Experiment Results System Application Algorithm Working Cost Good
Loading Capacity 90% ( 85%) Working Balance 50 70 (70%) Service 2
Good Routing Scheduling Dispatching Crisp { 0, 1 } Fuzzy [ 0, 1 ]
Linear Object-oriented Input Parameters few Objective Functions
many Objectives Balance improved Computational Time short HIMS: 60
min Expert: 4.5 hr. Flexibility Good process data type data
structure Individual Synthesis Atom Molecule Individual optimal
means Inter + Meta Meta + Fuzzy Slide 18 Related Works Journal
Papers 1. K. Chen, Y. Takama, and K. Hirota: A Calculation Model of
Hierarchical Multiplex Structure for Vehicle Routing &
Scheduling Dispatching Problem with Single Depot, J. of Japan
Society for Fuzzy Theory and Systems, Vol.13, No.2.(2001/4) 2. K.
Chen, Y. Takama, and K. Hirota: A Hierarchical Multiplex Structure
Model for Practical Transportation Problems with Multiple Depots,
International Journal of Fuzzy System Vol.2, No.4 (2000/12) 3. K.
Chen, Y. Takama, and K. Hirota: Vehicles Dispatching Problem for
Cooperative Delivery from Multiple Depots, Journal of Advanced
Computational Intelligence, Vol.4, No.6, (2000/12) Slide 19 Related
Works International Conference 4. K. Chen, Y. Takama, and K.
Hirota: A study to a synthetic solution for vehicle routing,
scheduling, & dispatching problem with single depot, The Fourth
Asian Fuzzy Systems Symposium, Tsukuba Science City, Japan, pp.
487-492, 2000/05/31. Oral Presentations 5. K. Chen, Y. Takama, and
K. Hirota: A Calculation Model of Hierarchical Multiplex Structure
for Vehicle Routing, Scheduling, & Dispatching Problem with
Multiple Depots, SOFT, 35-th Intelligence Control Symposium SIC99-2
, pp. 39-44, 2000/01/28. 6. K. Chen, Y. Takama, and K. Hirota:
Vehicle Dispatching Computational Model for Cooperative Deliveries
with Multiple Depots, SICE, 27-th Intelligent Systems Symposium pp.
55-60, 2000/03/23.
