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A bi-objective possibilistic programming model for open shop scheduling problems with sequence-dependent setup times, fuzzy processing times, and fuzzy due dates

Noori Darvish, S ; Sharif University of Technology | 2012

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  1. Type of Document: Article
  2. DOI: 10.1016/j.asoc.2011.11.019
  3. Publisher: 2012
  4. Abstract:
  5. We are concerned with an open shop scheduling problem having sequence-dependent setup times. A novel bi-objective possibilistic mixed-integer linear programming model is presented. Sequence-dependent setup times, fuzzy processing times and fuzzy due dates with triangular possibility distributions are the main constraints of this model. An open shop scheduling problem with these considerations is close to the real production scheduling conditions. The objective functions are to minimize total weighted tardiness and total weighted completion times. To solve small-sized instances for Pareto-optimal solutions, an interactive fuzzy multi-objective decision making (FMODM) approach, called TH method proposed by Torabi and Hassini, is applied. Using this method, an equivalent auxiliary single-objective crisp model is obtained and solved optimally by the Lingo software. For medium to large size examples, a multi-objective particle swarm optimization (MOPSO) algorithm is proposed. This algorithm consists of a decoding procedure using a permutation list to reduce the search area in the solution space. Also, a local search algorithm is applied to generate good initial particle positions. Finally, to evaluate the effectiveness of the MOPSO algorithm, the results are compared with the ones obtained by the well-known SPEA-II, using design of experiments (DOE) based on some performance metrics
  6. Keywords:
  7. Fuzzy parameters ; Open shop scheduling problem ; Particle swarm optimization ; Possibilistic programming ; Sequence-dependent setup times ; Total weighted completion times ; Total weighted tardiness ; Fuzzy parameter ; Particle swarm ; Sequence-dependent setup time ; Total-weighted tardiness ; Weighted completion ; Algorithms ; Computer programming ; Design of experiments ; Multiobjective optimization ; Production engineering ; Scheduling
  8. Source: Applied Soft Computing Journal ; Volume 12, Issue 4 , 2012 , Pages 1399-1416 ; 15684946 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S1568494611004613