Hybrid Tabu Search for Fuzzy Job Shop

Abstract

Abstract. We consider the fuzzy job shop scheduling problem, which is a variant of the well-known job shop problem, with uncertainty in task durations that we model using fuzzy numbers. We propose a tabu search algorithm for minimising the expected makespan based on reversing arcs within critical blocks. We test the algorithm and then combine it with a genetic algorithm from the literature so we can observe the synergy effect, obtaining better results with the hybrid algorithm than with its components by separate. Finally we compare our hybrid algorithm with a memetic algorithm from the literature and show that even in similar times, our method is better in terms of expected makespan.

The Fuzzy Optimization Algorithm to Solve Customer’s Highest Satisfaction Under Fuzzy Time

“…Jorge Puente et al [4] proposed a novel scheme for fuzzy JSP based on the change of the key block location of the task for searching community structure. Juan José Palacios et al [5] proposed an improved optimization algorithm by mixing the tabu search algorithm and the genetic algorithm. The improved algorithm was applied to solve the problem of fuzzy completion time.…”