Research And Application Of Decomposition Multiobjective Evolutionary Algorithm Based On Adaptive Neighborhood Adjustment Strategy

Multi-objective problems are common in all aspects of practical production problems.The key to study and solve this kind of problems is to choose the appropriate solution method.The final result of solving this kind of problem is a set of Pareto optimal solutions.Therefore,the multi-objective optimization problem and its solution method have important research value and practical significance.Because of its fast computing speed and high precision,evolutionary algorithm has a strong advantage in solving multi-objective problems.In recent years,in the research of multi-objective evolutionary algorithm,the multi-objective evolutionary algorithm based on Pareto domination is generally used to solve this kind of problem.However,the proportion of non dominated solution in this kind of algorithm is increasing with the number of targets,which leads to the performance degradation of the algorithm.The multi-objective evolutionary algorithm based on decomposition is not affected by Pareto domination.It decomposes the multi-objective problem which is difficult to be optimized into the single objective problem which is easy to be optimized for solution.Compared with the original multi-objective evolutionary algorithm based on Pareto domination,it has a strong advantage.Therefore,the algorithm has been widely concerned once it is proposed.Compared with the traditional multi-objective evolutionary algorithm based on Pareto dominance,its performance has been greatly improved.However,the algorithm uses a fixed neighborhood size to allocate the same computing resources for each subproblem.Because the complexity of each subproblem is different and the difficulty of optimization is different,one of the important factors that restrict the performance of the algorithm is to allocate the same size neighborhood to each subproblem,which results in the unreasonable allocation of computing resources.In this paper,a decomposition multi-objective evolutionary algorithm based on adaptive neighborhood adjustment strategy is proposed.In order to improve the performance of the decomposition based multi-objective evolutionary algorithm,the neighborhood of the reasonable assignment sub-problem is adjusted.The algorithm adjusts the neighborhood size of the same subproblem in different evolution algebras by the difference parameter ?.And it adjusts the neighborhood size of different sub-problems in the same evolution algebras by the included angle ?,so as to allocate the limited algorithm resources reasonably,balances the conflict between the convergence and diversity of the algorithm,improves the algorithm's solving ability and the overall quality of the solution set.Finally,this paper applies the proposed algorithm to the actual green supply chain partner selection problem,provides more and better solutions for decision makers in the selection of partners,and provides new ideas and methods for solving the complex multi-objective optimization problem with the actual logistics background.