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This paper addresses a fuzzy mixed-integer non-linear programming (FMINLP) model by considering machine-dependent and job-sequence-dependent set-up times that minimize the total completion time, the number of tardy jobs, the total flow time and the machine load variation in the context of unrelated parallel machine scheduling (UPMS) problem. The above-mentioned multi-objectives were considered based on non-zero ready times, machine- and sequence-dependent set-up times and secondary resource constraints for jobs. The proposed approach considers unrelated parallel machines with inherent uncertainty in processing times and due dates. Since the problem is shown to be NP-hard in nature, it is a challenging task to find the optimal/near-optimal solutions for conflicting objectives simultaneously in a reasonable time. Therefore, we introduced a new multi-objective-based evolutionary artificial immune non-dominated sorting genetic algorithm (AI-NSGA-II) to resolve the above-mentioned complex problem. The performance of the proposed multi-objective AI-NSGA-II algorithm has been compared to that of multi-objective particle swarm optimization (MOPSO) and conventional non-dominated sorting genetic algorithm (CNSGA-II), and it is found that the proposed multi-objective-based hybrid meta-heuristic produces high-quality solutions. Finally, the results obtained from benchmark instances and randomly generated instances as test problems evince the robust performance of the proposed multi-objective algorithm. [ABSTRACT FROM AUTHOR]

Real-time adaptive production control in the flexible manufacturing cell (FMC) is a complex issue that needs to be addressed to realize good performance and high productivity. In this paper, we have considered a support vector machine (SVM)-based simulation approach to resolve a production control problem in an FMC that operates in a dynamic environment. A SVM-based simulation approach chooses the most relevant scheduling rule out of several predefined ones on the basis of the current states of the system. This paper examines and compares the performance of the SVM-based simulation approach with the competent scheduling rules under two different operational environments which are characterized by the uncertainty of demand. We have also developed a Visual Basic-based simulation approach for scheduling of component parts in the context of FMC under different situations. The SVM methodology to control the production offers better performance than the single-rule-based production control system. [ABSTRACT FROM AUTHOR]

Complex systems in a work cell often consist of multiple units to process the manufacturing functions effectively for achieving the desired objectives. All manufacturing work cells are familiar with many unforeseeable events, for instance machine down time and scheduled maintenance. In fact, every configuration naturally exhibits some level of redundancy during those unpredictable events that may fail a small portion of units. In this work, using the remaining units and by raising the workloads on these units, up to the level of their capacities, we tried to fulfil the requirement of products. To procure the requirement, dynamic workload adjustment strategy has been suggested on two important configurations such as parallel and hybrid, by actively controlling its degradation path and failure times. During its operation, at each decision-making point, termed as decision epoch, the examination of the real-time condition monitoring data has been carried out for upgrading the posterior distribution. Using this updated distribution as the root of all operations, the residual life distribution of every concerned unit is calculated, for a particular workload. Subsequently, the establishment of an optimization scheme, i.e., an optimization framework, has been carried out with the help of the predicted residual life to eliminate the unit failures, for individual units, coinciding with each other. Eventually, with various scenarios, simulation has been carried out on the proposed methodology to assess the rate of degradation of various units. The validation of the approach's effectiveness has been shown by the simulation results on two different configurations having different scenarios. [ABSTRACT FROM AUTHOR]