Adjustment of term weights in an energy function used in the simulated annealing approach to vehicle scheduling problems

Hideo Itoyama, Harukazu Igarashi, Hironao Kawashima

Research output: Contribution to journalArticle

Abstract

Although the vehicle scheduling problem (VSP) is a difficult optimization problem with multiple objectives and many constraints, the simulated annealing (SA) method with a string model can solve it quickly and precisely. In the SA method, the importance of the objectives or constraints is expressed by the coefficients (weights) of the terms of the energy function. But the values of weights are usually determined by trial and error, In this paper, we propose a new method for adjusting the weights of terms automatically. This method can adjust the weights in the annealing process by using the "two-layer random field model" (TRFM). Aspiration levels given by the scheduling planner for every objective and constraint are defined and used as targets for adjusting the weights. Our new method is applied to an actual VSP which has 50 stores and 10 vehicles and confirms that adjustment of the weights of terms in the energy function is effective and suitable for the SA method.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalSystems and Computers in Japan
Volume28
Issue number2
DOIs
Publication statusPublished - 1997 Feb 1
Externally publishedYes

Keywords

  • Logistics
  • Neural network
  • Simulated annealing
  • Two-layer random field model
  • Vehicle scheduling problem

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture
  • Computational Theory and Mathematics

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