A Bi-objective Model for Collaborative Planning in Dyadic Supply Chain

The collaborative planning and the management of production and storage processes are important components in supply chain management. The goal of this paper is topresent the reliability of genetic algorithms on solving bi-objective models compared to mono-objective models. To do this we will be based initially on the mono-objective Dudek's model and then we propose a division of the objective function in two objective functions. Finally we compare the results given by the genetic algorithms with the optimality result obtained using the LINGO solver on the mono-objective Dudek's model. This model aims at simultaneously minimizing the total production cost and the total holding cost. To solve the proposed model, we use a genetic algorithm NSGA-II. The proposed several test provide results that demonstrate and validate the effectiveness of the multi-objective approach and elitists genetic algorithms in solving this type of problem, compared to the literature in the proposed test. The validation of our approach will allow us later to use this algorithm in solving complex multi-objective models approaching the real context.