This paper aims to study a real case of an optimization problem derived from a hospital supply chain. The present work focuses on developing operational decision support models and algorithms for production process scheduling in hospital catering. The addressed production system is considered as a flexible job shop system. The objective is to minimize the total flow time. A novel mathematical model and two metaheuristics for the production scheduling of multi-product and multi-stage food processes are developed. These methods have proven their effectiveness for the scheduling of operations of the food production processes and allowed significant improvements in the performance of the studied production system.
In this paper, a new approach to determine optimal disassembly plan of an end-of-life system by using Bayesian network is introduced. The best solution is called the optimal trajectory. A trajectory model is proposed which allows handling the different key factors and also makes it possible to manage uncertainties specific to system deconstruction. After having presented the disassembly planning issue, Bayesian networks instantiated to dismantling problem are introduced together with the influence diagram which allow the decision maker to proceed to the economic assessment of the different possible strategies. Among the various cost factors is the cost related to warranty of the recycled products. A warranty program management is described. Eventually, the global trajectory model, including the implementation of the warranty cost has a decision variable, is presented.
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