By using the proposed system, non-dominated solutions are compared and one solution is selected by considering trade-offs among performance measures of the solutions.
📌 3 Key Takeaways
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Objective & Hypothesis:This work proposes to use the fitness scores of jobs to machines in unrelated parallel machine scheduling to maximize machine preferences by using the fitness scores of jobs.
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Key Findings & Data:A bi-objective mathematical model for the unrelated parallel machine problem with sequence dependent setup times is designed to minimize makespan and maximize machine preferences of jobs.
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Conclusion & Impact:By using the proposed system, non-dominated solutions are compared and one solution is selected by considering trade-offs among performance measures of the solutions.
This work proposes to use the fitness scores of jobs to machines in unrelated parallel machine scheduling to maximize machine preferences by using the fitness scores of jobs. A bi-objective mathematical model for the unrelated parallel machine problem with sequence dependent setup times is designed to minimize makespan and maximize machine preferences of jobs. Bi-objective Simulated Annealing Algorithm is proposed for solving large sized problems. A Decision Support System designed for solving problems with objective function of the maximizing machine preferences in combination with other common scheduling objective functions for unrelated parallel machine scheduling problems. By using the proposed system, non-dominated solutions are compared and one solution is selected by considering trade-offs among performance measures of the solutions.
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