Climbing depth-bounded discrepancy search for solving hybrid flow shop problems
Date
2007Source Title
European Journal of Industrial Engineering
Print ISSN
1751-5254
Electronic ISSN
1751-5262
Publisher
Inderscience Publishers
Volume
1
Issue
2
Pages
223 - 240
Language
English
Type
ArticleItem Usage Stats
163
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192
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Abstract
This paper investigates how to adapt some discrepancy-based search
methods to solve Hybrid Flow Shop (HFS) problems in which each stage
consists of several identical machines operating in parallel. The objective is to
determine a schedule that minimises the makespan. We present here an
adaptation of the Depth-bounded Discrepancy Search (DDS) method to obtain
near-optimal solutions with makespan of high quality. This adaptation for the
HFS contains no redundancy for the search tree expansion. To improve the
solutions of our HFS problem, we propose a local search method, called
Climbing Depth-bounded Discrepancy Search (CDDS), which is a
hybridisation of two existing discrepancy-based methods: DDS and Climbing
Discrepancy Search (CDS). CDDS introduces an intensification process around
promising solutions. These methods are tested on benchmark problems. Results
show that discrepancy methods give promising results and CDDS method gives
the best solutions.
Keywords
SchedulingHybrid flow shop
HFS
Discrepancy search methods
Climbing depth-bounded discrepancy search
CDDS
Lower bounds
LBs
Heuristics