Objective Function Adjustment Algorithm for Combinatorial Optimization Problems

Hiroki TAMURA  Zongmei ZHANG  Zheng TANG  Masahiro ISHII  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E89-A   No.9   pp.2441-2444
Publication Date: 2006/09/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e89-a.9.2441
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Numerical Analysis and Optimization
guided local search,  local search,  objective function adjustment,  Tabu search,  

Full Text: PDF(576.1KB)>>
Buy this Article

An improved algorithm of Guided Local Search called objective function adjustment algorithm is proposed for combinatorial optimization problems. The performance of Guided Local Search is improved by objective function adjustment algorithm using multipliers which can be adjusted during the search process. Moreover, the idea of Tabu Search is introduced into the objective function adjustment algorithm to further improve the performance. The simulation results based on some TSPLIB benchmark problems showed that the objective function adjustment algorithm could find better solutions than Local Search, Guided Local Search and Tabu Search.