Solving a new bi-objective mathematical model for a hybrid flow shop scheduling problem with robots and fuzzy maintenance time

Abstract

This paper presents a bi-objective mathematical model of a hybrid flow shop scheduling problem (HFSSP) with robots and fuzzy maintenance time. The proposed model minimizes the mean completion time of jobs and the total cost of the processes based on maintenance costs and incurred transportation costs via robots. A fuzzy chance-constrained programming (FCCP) model is used to present its deterministic-equivalent problem. It is then solved by two multi-objective decision-making approaches, namely LP-metric and goal attainment (GA). A sensitivity analysis of the weights of the objective functions is conducted and the behavior of the model is studied for each instance. Also, a TOPSIS (the technique for order of preference by similarity to ideal solution) method is used to rank the efficiency of the proposed solution approaches. Future research areas are also suggested.