Modeling and Mip-Heuristics for the General Lotsizing and Scheduling Problem With Process Configuration Selection

Abstract

In some industrial contexts, such as in the molded pulp, paper, furniture and electrofused grain industries, items or final products are obtained by processes that can produce several types of products simultaneously. These processes are considered here as any specific mode of operation or configuration of a production system that can produce several different items simultaneously and in varied quantities. The production planning and scheduling in these industrial contexts involve decisions of: i) configuration selection of these processes; ii) production lot sizing of selected configurations; and iii) decisions of scheduling these selected configurations. In this work, a mixed integer programming model (MIP) is presented to adequately represent this integrated problem, called the general lotsizing and scheduling problem with process configuration selection. In order to achieve effective production plans at acceptable computational times in practice, Relax-and-Fix and Fix-and-Optimize heuristics based on this model are also presented. Computational experiments were performed solving the model with an optimization solver and applying the proposed heuristics in examples inspired in molded pulp, furniture and electrofused grain packaging companies. The results show that MIP-heuristics can solve the problem more effectively (good quality solution in acceptable time) than simply using the solver for the mathematical model.