Heuristics and Metaheuristics for heavily constrained hybrid Flowshop Problems

Urlings, T.
Pub. date
January 2011
331 of Dissertations in Artificial Intelligence
ISBN print
Artificial Intelligence, Computer & Communication Sciences, Computer Science
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Many researchers agree about the existence of a gap between machine scheduling literature on the one hand and scheduling in real-world production environments on the other hand. This book aims to contribute in diminishing this gap.

A hybrid flowshop problem with a combination of many constraints that occur in reality, is addressed. An exact solution method is developed, and some heuristics. Also, a number of metaheuristics is adapted to the problem and several new ones are presented. Comparison is done, enhancing statistical analyses. The solution representation appears to have an important influence on the quality of the results.

Multiobjective scheduling is a common need in practice. For Pareto optimization in a hybrid flowshop, two algorithms and a complete methodology for the comparison of approximation algorithms are presented.

From the obtained results, one can conclude that methods that work well for relatively simple, theoretical problems do often not behave so well for more complex real-life environments. Therefore, research to this latter kind of problem is highly relevant.