Özet:

Purpose- In this study, an intelligent scheduling to efficiently make supplier-task assignments is proposed. As the logistic support regarding supply chain management, a scheduling program was developed to determine the suppliers to perform the existing tasks with the orders. Each of a number of suppliers performs a subset of all tasks with a certain order and it is aimed to perform all of them with the minimum cost. The limited number of tasks to be performed by each supplier is predetermined. Methodology- The main contribution here is to model the problem so that each task can have a different precedence/weight. The multi-objective cost function hereby designed consists of two sub-costs: (1) the cost between source-task pair, and (2) the weights referring to the ordering precedence regarding the completion of the tasks to be performed by the same source. For the solution, a genetic algorithms based meta-heuristic was used. Findings- To test the success of the algorithm, instances including different numbers of tasks and suppliers were created with various task weights. The results obtained by executing the developed algorithm on these instances are presented. Conclusion- Moreover, it was observed that accurate and appropriate schedules could be generated within significant times.

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