Repair equipment allocation problem for a support-and-repair ship on a deep sea: A hybrid multi-criteria decision making and optimization approach

Abstract

To address the repair equipment allocation problem for a support-and-repair ship on a deep sea, a hybrid multi-criteria decision making and optimization approach is designed. Evidence reasoning approach is used to aggregate the evaluation information of quantitative criteria (i.e., weight and economics) and qualitative criteria (i.e., repair ability, reliability and convenience). Then, a mathematical repair equipment allocation model of a support-and-repair ship is formulated, which is a mixed-integer nonlinear model. A removal strategy based on a greedy algorithm that modifies infeasible solutions is designed to facilitate the use of a genetic algorithm with an elite strategy to address the model above. The proposed solution method using the removal strategy based on the greedy algorithm obtains better solution accuracy and global search performance than three widely used penalty-based methods by several test instances generated randomly. The results of a case study prove that the mathematical model and solution method can effectively obtain the optimal repair equipment allocation solution. The hybrid multi-criteria decision making and optimization approach has certain guiding significance for decision makers to determine their repair equipment allocation strategies for support-and-repair ships on a deep sea in practice.