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Fuzzy optimisation of multi-objective job shop scheduling based on inventory information

Author

Listed:
  • Mohammad Nouroz Islam
  • Sanjoy Kumar Paul
  • Abdullahil Azeem

Abstract

Job shop scheduling problems are one of the oldest combinatorial optimisation problems being studied. In this paper, fuzzy processing times of operations and fuzzy due dates of jobs are considered to incorporate fuzziness in the problem. Percentage of inventory consumption and profit earned form the orders are also considered in this fuzzy multi-objective job shop scheduling problem. Fuzzy inference system (FIS) is used to calculate the job weights based on the percentage of inventory consumption for a particular job and profit can be earned from the jobs. Average weighted tardiness, number of tardy jobs, total flow time and idle times of machines are considered as objectives which should be minimised. In this paper, genetic algorithm (GA) is used as a heuristic technique with specially encoded chromosomes that denotes the complete schedule of the jobs. A local search technique, simulated annealing (SA) is also used to compare the results obtained in two different methods. Different problem sizes has been tested and the fitness function values and computation times of the problems for each method is compared.

Suggested Citation

  • Mohammad Nouroz Islam & Sanjoy Kumar Paul & Abdullahil Azeem, 2013. "Fuzzy optimisation of multi-objective job shop scheduling based on inventory information," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 15(2), pages 123-139.
    • Handle: RePEc:ids:ijsoma:v:15:y:2013:i:2:p:123-139
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