Genetic algorithm and Tabu search for vehicle routing problems with stochastic demand

Zuhaimy Ismail

doi:10.1063/1.3525151

Genetic algorithm and Tabu search for vehicle routing problems with stochastic demand

Zuhaimy Ismail^*, Irhamah

^*Corresponding author for this work

Laboratory of Computational Statistics and Data Science

Universiti Teknologi Malaysia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

This paper presents a problem of designing solid waste collection routes, involving scheduling of vehicles where each vehicle begins at the depot, visits customers and ends at the depot. It is modeled as a Vehicle Routing Problem with Stochastic Demands (VRPSD). A data set from a real world problem (a case) is used in this research. We developed Genetic Algorithm (GA) and Tabu Search (TS) procedure and these has produced the best possible result. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities.

Original language	English
Title of host publication	ICMS - International Conference on Mathematical Science
Pages	488-504
Number of pages	17
DOIs	https://doi.org/10.1063/1.3525151
Publication status	Published - 2010
Event	International Conference on Mathematical Science, ICMS - Bolu, Turkey Duration: 23 Nov 2010 → 27 Nov 2010

Publication series

Name	AIP Conference Proceedings
Volume	1309
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	International Conference on Mathematical Science, ICMS
Country/Territory	Turkey
City	Bolu
Period	23/11/10 → 27/11/10

Keywords

Genetic Algorithm
Tabu Search
Vehicle Routing Problem with Stochastic Demands
hybrid algorithm

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1063/1.3525151

Cite this

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title = "Genetic algorithm and Tabu search for vehicle routing problems with stochastic demand",

abstract = "This paper presents a problem of designing solid waste collection routes, involving scheduling of vehicles where each vehicle begins at the depot, visits customers and ends at the depot. It is modeled as a Vehicle Routing Problem with Stochastic Demands (VRPSD). A data set from a real world problem (a case) is used in this research. We developed Genetic Algorithm (GA) and Tabu Search (TS) procedure and these has produced the best possible result. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities.",

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AU - Ismail, Zuhaimy

AU - Irhamah,

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N2 - This paper presents a problem of designing solid waste collection routes, involving scheduling of vehicles where each vehicle begins at the depot, visits customers and ends at the depot. It is modeled as a Vehicle Routing Problem with Stochastic Demands (VRPSD). A data set from a real world problem (a case) is used in this research. We developed Genetic Algorithm (GA) and Tabu Search (TS) procedure and these has produced the best possible result. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities.

AB - This paper presents a problem of designing solid waste collection routes, involving scheduling of vehicles where each vehicle begins at the depot, visits customers and ends at the depot. It is modeled as a Vehicle Routing Problem with Stochastic Demands (VRPSD). A data set from a real world problem (a case) is used in this research. We developed Genetic Algorithm (GA) and Tabu Search (TS) procedure and these has produced the best possible result. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities.

KW - Genetic Algorithm

KW - Tabu Search

KW - Vehicle Routing Problem with Stochastic Demands

KW - hybrid algorithm

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M3 - Conference contribution

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SP - 488

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BT - ICMS - International Conference on Mathematical Science

T2 - International Conference on Mathematical Science, ICMS

Y2 - 23 November 2010 through 27 November 2010

ER -

Genetic algorithm and Tabu search for vehicle routing problems with stochastic demand

Abstract

Publication series

Conference

Keywords

UN SDGs

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