Authors: Kemal Alaykýran Orhan Engin Alper Döyen
Publish Date: 2007/05/24
Volume: 35, Issue: 5-6, Pages: 541-550
Abstract
In recent years most researchers have focused on methods which mimic natural processes in problem solving These methods are most commonly termed “natureinspired” methods Ant colony optimization ACO is a new and encouraging group of these algorithms The ant system AS is the first algorithm of ACO In this study an improved ACO method is used to solve hybrid flow shop HFS problems The njob and kstage HFS problem is one of the general production scheduling problems HFS problems are NPhard when the objective is to minimize the makespan 1 This research deals with the criterion of makespan minimization for HFS scheduling problems The operating parameters of AS have an important role on the quality of the solution In order to achieve better results a parameter optimization study is conducted in this paper The improved ACO method is tested with benchmark problems The test problems are the same as those used by Carlier and Neron RAIRORO 3411–25 2000 Neron et al Omega 296501–511 2001 and Engin and Döyen Future Gener Comput Syst 2061083–1095 2004 At the end of this study there will be a comparison of the performance of the proposed method presented in this paper and the branch and bound BB method presented by Neron et al Omega 296501–511 2001 The results show that the improved ACO method is an effective and efficient method for solving HFS problems
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