In this paper, we consider job shop scheduling problem (JSSP) and machine location problem, simultaneously. In fact, the machine location problem is incorporated into the JSSP. Setup time, processing time, transportation time, and due date are assumed to be fuzzy parameters. The purpose of this paper is to determine machine location and job scheduling so that the total cost including weighted tardiness and earliness penalties as well as transportation cost between machines is minimized. We refer to this problem as Fuzzy Job Shop Scheduling and Location Problem (FJSSLP). Due to fuzzy parameters and combination of job shop scheduling problem and machine location problem, the proposed model is more complex than job shop scheduling problem which is an NP-hard problem. Hence, genetic algorithm (GA) is developed to solve FJSSLP. To evaluate the efficiency of GA, we compare numerically the results of GA with simulated annealing algorithm (SA). Furthermore, sensitivity analysis is provided to clarify the effects of fuzzy parameters on the total cost.

Keywords