Solving Bi-Objective Stage Shop Scheduling Problem by Flower Pollination Algorithm with Fuzzy Orientation

Abstract

Stage shop scheduling is a type of scheduling problem in manufacturing in which the operations to be performed on a set of jobs is divided into stages based on the type of operations. The stages are executed sequentially whereas the operations in each stage are executed in no particular order. A bi-objective stage shop scheduling problem has been proposed in this paper. There are two objectives as considered in this paper minimization of makespan and minimization the total completion times of a set of jobs on a manufacturing floor. The paper considers uniform fuzzy processing times for the jobs. The problem is basically solved by Multi-Objective version of Flower Pollination Algorithm (MOFPA). Flower pollination can be either global pollination (biotic pollination) or local pollination (abiotic). This paper applies both the types of pollination based on some probability values. Experimentation shows that MOFPA performs almost to an equivalent extent to the famous Nondominated Sorting Genetic Algorithm – II (NSGA-II). The algorithm has been compared with NSGA-II since NSGA-II is one of the most frequently applied multi-objective methods as evident from the existing literature.