Multi-Objective Flexible Job-Shop Scheduling with Limited Resource Constraints in Hospital Using Hybrid Discrete Firefly Algorithm

Abstract

A hybrid discrete firefly algorithm (HDFA) is used in this paper for solving a multi objective flexible job shop problem (FJSP) with resource limitation constraint occurred in hospital in daily life. In any scheduling related problem, main constraint is each of the operation of the required job have to maintain a sequence of processing and each of that operations should be processed on a particular assigned machine. The limitations in resources and flexibility of the machine are balanced using these common constraints. On the other hand, FJSP is basically the extension of classical problem of job shop that will allow the operations to be processed at any of the machines from the given set along the different path for processing. In this research, three main objectives were considered. Highest completion time for a set, the critical machines workload and machines total workload determination are considered as the objectives. The discretization of firefly algorithm consists of the construction of functions conversion as the movement, attractiveness and distance is proposed here. The algorithm used in this paper is discrete firefly algorithm (DFA), which is basically a combination of the local search (LS) for the enhancement of accuracy in searching and sharing of the information among the fireflies. Here, LS with the neighborhood structure is utilized to increase the exploitation capability when it is hybridized. The benchmark instances and comparison with the result of other algorithm shows that, the result of this particular algorithm is comparatively effective and feasible than the others for a multi objective flexible job shop problem in hospitals.

Keywords: Flexible Job Shop Problem (FJSP), Hybrid discrete firefly algorithm (HDFA), Local search (LS), Multi objective optimization, Discrete firefly algorithm (DFA)