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The study for transportation planning considered the inventory using hybrid genetic algorithm

Authors:

Shinichiro Ataka,

Mitsuo GenAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 1689 - 1690

https://doi.org/10.1145/1389095.1389411

Published: 12 July 2008 Publication History

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Abstract

The transportation planning (TP) is well-known basic network problem. However, for some real-world applications, it is often that the TP model is extended to satisfy other additional constraints or performed in several stages. In this study, we formulate the two-stage transportation planning with inventory and exclusionary side constraints (esc-2ITP). In this model, one week divided into some terms and the annual demands of delivery centers are satisfied for each them and it includes the additional constraint in which the simultaneous shipments between some plants are prohibited. To solve the problem, we propose the hybrid Genetic Algorithms (h-GA) approach by using a priority-based encoding method.

References

[1]

M. Gen, R. W. Cheng and L. Lin, "Network Models and Optimization: Multiobjective Genetic Algorithm Approach", Springer, In Press, 2008.

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[2]

M. Sun, "The transportation problem with exclusionary side constraints and two branch-and-bound algorithms", European Journal of Operational Research, vol. 140, no. 3, pp. 629--647, 2002.

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The study for transportation planning considered the inventory using hybrid genetic algorithm
1. Applied computing
  1. Physical sciences and engineering
    1. Mathematics and statistics
2. Mathematics of computing
  1. Discrete mathematics
    1. Graph theory

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GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

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Association for Computing Machinery

New York, NY, United States

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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An Effective Hybrid Genetic Simulated Annealing Algorithm for Process Planning Problem

A hybrid genetic algorithm for two-stage multi-item inventory system with stochastic demand

Extension of a hybrid genetic algorithm for nonlinear programming problems with equality and inequality constraints

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