Integrated production planning and scheduling under uncertainty: A fuzzy bi-level decision-making approach

Abstract

Production planning and scheduling are two core decision layers, constrained and affected by one another in manufacturing systems. Owing to different time scales and objectives, planning and scheduling are often separately handled in a sequential way, which frequently results in infeasible or suboptimal solutions. Moreover, uncertain issues, e.g. the fuzzy startup time of a machine and the fuzzy processing time for a task, are inherent to manufacturing systems due to mechanized and/or man-made factors. Motivated by these challenges, this paper aims to develop fuzzy bi-level decision-making techniques to handle integrated planning and scheduling problems in the fuzzy manufacturing system. First, the integrated problem is formulated into a fuzzy bi-level decision model in which solving the higher-level planning problem has to take into account lower-level implicit scheduling reactions in advance. Second, a hybrid solution method is developed to solve the resulting bi-level decision model, in which a particle swarm optimization (PSO) algorithm is applied to update planning decisions, and then, in view of each given planning decision, a heuristic algorithm is presented to find an optimal schedule under fuzzy manufacturing conditions. Lastly, a set of computational study is constructed to demonstrate the effectiveness of the proposed fuzzy bi-level decision-making techniques. Compared with existing works, they can find better planning decisions fulfilled by schedules and perform much better in terms of computational efficiency.