Hybrid genetic algorithm for minimizing total weighted tardiness in job shop scheduling problem

作者：Cai Bin^*; Wang Shilong

来源：International Journal of Advancements in Computing Technology, 2012, 4(12): 128-135.

DOI：10.4156/ijact.vol4.issue12.16

• Active schedules
• Computational results
• Due dates
• Hybrid genetic algorithms
• Job shop scheduling problems
• Local search heuristics
• Mating process
• Mutation operators
• Search spaces
• Service reputation
• Total-weighted tardiness

In modern manufacturing systems, due date related performance is becoming increasingly important in maintaining a high service reputation. This paper presents a hybrid genetic algorithm for job shop scheduling problem (JSSP) with the objective of minimizing total weighted tardiness. A new generation alternation model of genetic algorithm for JSSP is designed. Every pair of randomly selected parents must pass either crossover or mutation, which are deployed in parallel. When the mating process is carried out, crossover or mutation operator is applied to the parents many times and the best individual in those offspring is selected to the next generation. The decoding procedure limits the search space to the set of active schedules. In each generation, a neighborhood based local search heuristic is applied to improve the solutions. The computational results on a set of standard instances validate the effectiveness of the proposed algorithm.

• 出版日期2012