In this work, we develop a novel mathematical formulation for the energy-efficient flexible job-shop scheduling problem using the improved unit-specific event-based time representation. The flexible job-shop is repres...
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In this work, we develop a novel mathematical formulation for the energy-efficient flexible job-shop scheduling problem using the improved unit-specific event-based time representation. The flexible job-shop is represented using the state-task network. It is shown that the proposed model is superior to the existing models with the same or better solutions by up to 13.5 % energy savings in less computational time. Furthermore, it can generate feasible solutions for large-scale instances that the existing models fail to solve. To efficiently solve large-scale problems, a grouping-based decomposition approach is proposed to divide the entire problem into smaller subproblems. It is demonstrated that the proposed decomposition approach can generate good feasible solutions with reduced energy consumption for large-scale examples in significantly less computational time (within 10 min). It can achieve up to 43.1 % less energy consumption in comparison to the existing gene-expression programming-based algorithm. (c) 2021 Elsevier Ltd. All rights reserved.
This paper investigates an integrated batching and scheduling problem of electrolysis and caster in aluminium industry. The problem is to determine the assignment and scheduling of orders considering sequence-dependen...
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This paper investigates an integrated batching and scheduling problem of electrolysis and caster in aluminium industry. The problem is to determine the assignment and scheduling of orders considering sequence-dependent setup times caused by technological and operational constraints of electrolysis cells, and determine the batching and scheduling of orders in the following casters. A novel unit-specific event-based continuous-time mixed integer linear programming model (MILP) is proposed to describe the problem. In this model, the event point is stage specific, and lower bounds are specified to tighten the model. A hybrid pointer-based differential evolution algorithm with new individual representation scheme is designed to solve the problem of industrial scale. An improved hybrid pointer-based mutation operator and a new point-cross crossover operator are proposed to enhance the performance of the algorithm. Computational experiments show that the proposed algorithm is more efficient when compared with CPLEX for medium and large size instances. Comparisons with the lower bound demonstrate that the algorithm is effective.
The problem of short-term scheduling of batch plants has received remarkable attention in the past two decades. The state-task-network (STN) and resource-task-network (RTN) process representations are extensively used...
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The problem of short-term scheduling of batch plants has received remarkable attention in the past two decades. The state-task-network (STN) and resource-task-network (RTN) process representations are extensively used in modeling scheduling problems. In this paper, we propose a new model to investigate the RTN representation for unit-specific event-based models. For handling dedicated finite storage, a novel formulation is proposed without the need for considering storage as a separate task. The performance of the proposed model is evaluated along with several other continuous-time models from the literature based on the STN and RTN process representations. The various models are assessed based on our implementations using several benchmark example problems from the literature. Two different objective functions, maximization of profit and minimization of makespan, are considered. Two storage policies, unlimited and dedicated finite storage cases are also considered. (C) 2007 Elsevier Ltd. All rights reserved.
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