This study aimed to develop a model for vehicle routing problem with two objective functions of risk and distance minimization to optimize safety of cash/valuable commodities transportation. It is necessary to properly anticipate and prevent the occurrence of robbery to reduce the vulnerability to robbery attempts. The proposed approach for the vulnerability estimation of an armed robbery has been based on game theory and multi-criteria decision making (MCDM), which can accurately measure the amount of risk. A new multi-objective intelligent genetic algorithm (MOIGA) comprised of various heuristics is also designed to identify and intelligently select the most efficacious heuristic. The following experiments are used to test the proposed MOIGA: (1) Examining the influence of each proposed operator on the performance of the algorithm; (2) Evaluating the quality and diversity of MOIGA solutions compared to other popular algorithms. The obtained results demonstrate the effectiveness and efficiency of the proposed algorithm.

这项研究旨在开发一种具有风险和距离最小化两个目标函数的车辆路径问题模型，以优化现金/贵重物品运输的安全性。有必要正确地预见并防止抢劫的发生，以减少抢劫企图的脆弱性。拟议的武装抢劫脆弱性评估方法基于博弈论和多准则决策（MCDM），可以准确地衡量风险程度。还设计了一种由各种启发式方法组成的新的多目标智能遗传算法（MOIGA），以识别和智能地选择最有效的启发式方法。以下实验用于测试提出的MOIGA：（1）检查每个提出的算子对算法性能的影响；（2）与其他流行算法相比，评估MOIGA解决方案的质量和多样性。获得的结果证明了该算法的有效性和有效性。