Modeling long-term production scheduling problem and its solution using a bat meta-heuristic method

Abstract

The long-term production scheduling problem, in which a schedule must obey physical constraints and operational constraints between pairs of activities, is one of the most studied scheduling problems. An important variation of this problem is to find a schedule which maximizes the net present value. Since production scheduling problems are NP-hard, there is a need of improving scheduling methodologies to get good solutions. At present, the research on scheduling theory has been paid an overwhelming attention, and has made great progress. However, it is still not mature enough. Among them, the research on complexity of the scheduling problem has become a branch of applied mathematics with a strong engineering background. The mathematical model of production scheduling problem is established, and a novel improved bat algorithm (BA) is proposed. For the purpose of expressing the relationship effectively between the process and the bat population, a new method of encoding strategy based on dual flexibility degree is proposed. For the purpose of overcoming the shortcomings of the fixed parameters in the bat algorithm, the value of the inertia weight was adjusted, and a linear decreasing inertia weight strategy was proposed. This shows that the proposed algorithm is more excellent in solving the production scheduling problem, and it is an efficient scheduling algorithm.