Abstract
In recent years, the concerns on energy efficiency in manufacturing systems have been growing rapidly due to the pursuit of sustainable development. Production scheduling plays a vital role in saving energy and promoting profitability for the manufacturing industry. In this paper, we are concerned with a just-in-time (JIT) single machine scheduling problem which considers the deterioration effect and the energy consumption of job processing operations. The aim is to determine an optimal sequence for processing jobs under the objective of minimizing the total earliness/tardiness cost and the total energy consumption. Since the problem is NP -hard, an improved multi-objective particle swarm optimization algorithm enhanced by a local search strategy (MOPSO-LS) is proposed. We draw on the idea of k-opt neighborhoods and modify the neighborhood operations adaptively for the production scheduling problem. We consider two types of k-opt operations and implement the one without overlap in our local search. Three different values of k have been tested. We compare the performance of MOPSO-LS and MOPSO (excluding the local search function completely). Besides, we also compare MOPSO-LS with the well-known multi-objective optimization algorithm NSGA-II. The experimental results have verified the effectiveness of the proposed algorithm. The work of this paper will shed some light on the fast-growing research related to sustainable production scheduling.
Highlights
The manufacturing industry has been regarded as an intensive energy consumer
The aim is to obtain the best sequence for processing the set of jobs to minimize the total weighted earliness/tardiness (TWET) and the total energy consumption (TEC)
To find the best settings, we applied a design of experiments (DOE) approach to study the influence of these six parameters
Summary
The manufacturing industry has been regarded as an intensive energy consumer. To achieve sustainable development goals, a number of regulations are urging the manufacturers to adopt energy-saving measures. Some energy-intensive manufacturers (like steel companies) have adopted energy-saving production scheduling techniques, and the procedure is waiting to be extended and applied to other industries. Wu et al [6] investigate the flexible job-shop scheduling problem with the objective of minimizing total energy consumption and makespan They consider the deterioration effect as well. To the best of our knowledge, there are no results in the existing literature for production scheduling problems that integrate the JIT objective, the energy-saving requirement and explicit consideration of the deterioration effect. Note that the single-machine JIT scheduling problem with a deterioration effect is N P-hard [14], which means the time required by an exact algorithm to solve the problem increases exponentially with the number of jobs.
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