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During path planning, it is necessary to satisfy the requirements of multiple objectives. Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker. The decision-maker, however, has illegibility for understanding the requirements of multiple objectives and the subjectivity inclination. It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning. Based on Voronoi diagram method for the path planning, this paper studies the synthesis method of the multi-objective cost performance index. According to the application of the cost performance index to the path planning based on Voronoi diagram method, this paper analyzes the cost performance index which has been referred to at present. The analysis shows the insufficiency of the cost performance index at present, i.e., it is difficult to synthesize sub-objective functions because of the great disparity of the sub-objective functions. Thus, a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy, and an improved performance index is established, which could coordinate the weight conflict of the sub-objective functions. Finally, the experimental result shows the effectiveness of the proposed approach.

PurposeAirdrop operation has become an important transportation mode due to its mobility and rapidity and mission planning is one of the critical steps in the preparation of an airdrop operation. The purpose of this paper is to propose an efficient mission planning method for airdrop operation using multiple vehicles.Design/methodology/approachA hierarchical mission planning method is proposed. According to the objectives of the action, the mission planning is divided into three planning levels to form the hierarchical structure and the constraints are distributed among them. By doing so, the proposed approach converts the original mission planning problem to a constrained optimization problem, which is solvable using existing mathematical methods.FindingsOn the basis of analysis, the mathematic models of three planning levels are established. Each level has its own optimization objective, taking part of constraints into account. The integrated mission scheme had been obtained step by step.Practical implicationsThis paper systematically tackles the complicated multiple vehicles airdrop mission planning problem, and it provides a platform for optimizing the outcomes. The mathematical models established in this paper could apply in a variety of more complex mission scenarios.Originality/valueThis paper fulfils an urgent need to study how the advantages of airdrop operation can be maximized through planning airdrop mission schemes carefully.