ABSTRACT

Open shop scheduling problem is a common scheduling problem and has wide engineering applications in manufacturing. In some industrial cases, open shop scheduling could be a long scheduling problem as an aircraft production. In these cases, time value of money plays a significant role in determining a schedule cost. This paper addresses the problem of minimizing sum of weighted mean flow time and intermediate storage cost in an open shop scheduling environment. The main contribution of this work is to concern time-dependent weights which results in a more realistic insight for decision makers via considering time value of money in long scheduling problems. We have formulated the problem as a mixed integer linear programming model. Due to the nondeterministic polynomial time complexity of the problem, a novel genetic algorithm is also presented to solve the problem in reasonable time. Computational results indicate remarkable improvement of the objective function as compared with the case of having constant weights over scheduling horizon.