Presenting a fuzzy mathematical programming model for allocating and scheduling parts in a flexible manufacturing system (FMS) and the impact of repairs and maintenance on product quality
This study aims to develop a mathematical model for flexible job shop scheduling. The main focus is on optimizing three
the makespan, the maximum machine workload, and the total workload. The ultimate goal is to enhance productivity and flexibility in manufacturing systems.
Two metaheuristic algorithms, NSGA-II and MOGWO, were used to solve the model. The model was first validated on a small scale, and then sensitivity analysis was conducted on larger instances. The performance of the algorithms was compared based on accuracy and solution quality metrics.
Results indicated that MOGWO performs better in medium-sized problems, while in large-scale cases, the difference between the two algorithms is not significant. The highest sensitivity among the objectives was observed with respect to production and maintenance costs. Additionally, a resource allocation pattern and optimal sequence of operations were derived.
The originality of this research lies in developing and applying a multi-objective mathematical model for flexible job shop scheduling, considering real-world constraints such as costs and resource limitations. The simultaneous use and detailed comparison of NSGA-II and MOGWO across different problem sizes is another contribution. Furthermore, the proposed operational pattern improves the applicability of the results in industrial environments.
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Modeling Bias Errors on Managers' Financial Decision Making A Multi-Level Approach
Samira Saraei, Fatemeh Sarraf *, Mohsen Hamidian
Journal of Accounting and Auditing Research, -
Presenting a model for evaluating the social responsibility planning and management of banks (including a case study)
Ehsan Beigi, Mohammadreza Rasouli *, Seyed Vahid Aghili
Educational Administration Research Quarterly,