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      • Department of Management
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      Customer order scheduling problem: a comparative metaheuristics study

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      Author(s)
      Hazır, Ö.
      Günalay, Y.
      Erel, E.
      Date
      2007
      Source Title
      International Journal of Advanced Manufacturing Technology
      Print ISSN
      0268-3768
      Electronic ISSN
      1433-3015
      Publisher
      Springer
      Volume
      37
      Pages
      589 - 598
      Language
      English
      Type
      Article
      Item Usage Stats
      146
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      190
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      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.
      Keywords
      Computational complexity
      Genetic algorithms
      Heuristic methods
      Problem solving
      Resource allocation
      Simulated annealing
      Tabu search
      Ant colony optimization
      Customer order scheduling
      Metaheuristics
      Scheduling
      Permalink
      http://hdl.handle.net/11693/23128
      Published Version (Please cite this version)
      http://dx.doi.org/10.1007/s00170-007-0998-8
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      • Department of Management 579
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