Customer order scheduling problem: a comparative metaheuristics study

Date
2007
Authors
Hazır, Ö.
Günalay, Y.
Erel, E.
Advisor
Instructor
Source Title
International Journal of Advanced Manufacturing Technology
Print ISSN
0268-3768
Electronic ISSN
1433-3015
Publisher
Springer
Volume
37
Issue
Pages
589 - 598
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
Abstract

The customer order scheduling problem (COSP) is defined as to determine the sequence of tasks to satisfy the demand of customers who order several types of products produced on a single machine. A setup is required whenever a product type is launched. The objective of the scheduling problem is to minimize the average customer order flow time. Since the customer order scheduling problem is known to be strongly NP-hard, we solve it using four major metaheuristics and compare the performance of these heuristics, namely, simulated annealing, genetic algorithms, tabu search, and ant colony optimization. These are selected to represent various characteristics of metaheuristics: nature-inspired vs. artificially created, population-based vs. local search, etc. A set of problems is generated to compare the solution quality and computational efforts of these heuristics. Results of the experimentation show that tabu search and ant colony perform better for large problems whereas simulated annealing performs best in small-size problems. Some conclusions are also drawn on the interactions between various problem parameters and the performance of the heuristics.

Course
Other identifiers
Book Title
Keywords
Computational complexity, Genetic algorithms, Heuristic methods, Problem solving, Resource allocation, Simulated annealing, Tabu search, Ant colony optimization, Customer order scheduling, Metaheuristics, Scheduling
Citation
Published Version (Please cite this version)