Multiobjective resource allocation problem by multistage decision-based hybrid genetic algorithm

摘要

Multiobjective resource allocation problem (MORAP) is the process of allocating resources among the various projects or business units to meet the expected objectives. Resources may be manpower, assets, raw materials, capital or anything else in limited supply which can be used to accomplish the goals. The goal may be objectives or targets (i.e., maximizing profits, minimizing costs, or achieving the best possible quality), usually driven by specific future needs. For this reason, the MORAP will be formulated as a complex multiobjective optimization model. Hence, we tackle this problem via a multistage decision making model. A multistage decision making model is similar to a complex problem solving, in which a suitable sequence of decisions is to be found. The task can be interpreted as a series of interactions between a decision maker and an outside world, at each stage of which some decisions are available and their immediate effect can be easily computed. Eventually, goals would be reached due to the found of optimized variables.In this paper, in order to obtain a set of Pareto solutions efficiently, we propose a multiobjective hybrid genetic algorithm (mo-hGA) approach based on the multistage decision making model. According to the proposed method, we apply the mo-hGA to seek feasible solutions for all stages. The effectiveness of the proposed algorithm was validated by its application to an illustrative example dealing with multiobjective resource allocation problem.