Abstract:
In this study examines job shop scheduling problems with sequence dependent setup
times under objective function minimization of makespan (JSSP/SDST/
Cmax
). An effective
meta-heuristic, local search is a meta-heuristic method for solving computationally hard
optimization problems. Local search can be used on problems that can be formulated as
finding a solution maximizing or minimizing a criterion among a number of candidate
solutions. Local search algorithms move from solution to solution in the space of candidate
solutions (the search space) by applying local changes, until a solution deemed optimal is
found or a time bound is elapsed. The performance of the local search depends on its
neighborhood search structure (NSS). We used five methods from neighborhood search:
Swap, Migration Mechanism (MM), Inversion, shift, and a proposed robust neighborhood
search method. The results showed that the new PNS method gives less makespan value with
different problems size (15x15, 20x15, 20x20, 30x15, 30x20, 50x15, 50x20 and 100x20)
taken from the OR- library compared to previous well known neighborhood search methods.
