Due to the national policy of encouraging the development of power exchange modes, the reasonable planning of vehicle distribution paths to meet the demand of lithium battery power exchange points has become a topic of considerable research interest. In this study, we propose the “centralized charging + unified distribution” power exchange mode for optimizing the charging and transporting of lithium batteries. Considering lithium batteries are dangerous goods, the vehicle path problem of simultaneous pickup and delivery of lithium batteries with vehicle load and soft time window constraints is studied. The model objective is to minimize the transportation risk and total cost of delivery. By performing crossover and mutation operations on the initial solutions generated by the ant colony algorithm, a hybrid ant colony genetic algorithm (ACO-GA) is designed to solve the model. The results of ACO-GA are compared with the GA, ACO, and SAA methods using the Solomon dataset; the results show that the optimized ant colony algorithm can achieve a smaller total cost in solving the model. Finally, taking a lithium battery leasing business in Company A, we determine the optimal path under different preferences by setting different weights for distribution cost and transportation risk in the model transformation, which provides a reference for the company to select the distribution route. Thus, the model provides a reference for companies that intend to develop power exchange businesses.

Viewing from the perspective of a traditional manufacturing enterprise, the paper proposes a fuzzy comprehensive evaluation system model, which selects the most suitable supplier or suppliers to undertake the supply tasks and to achieve the purposes of reducing procurement costs and improving the supply quality and reliability, so as to fully meet customer demands. Based on decision-makers’ preferences and suppliers’ supply capabilities, subjective and objective weight of criteria are both developed for supplier selection with the corresponding weighting method, namely, quality function deployment (QFD) and entropy weight. Specially, the two-phase fuzzy QFD method combined with the trapezoidal fuzzy number (TFN) is creatively applied to realize the complicated conversion process. Furthermore, the game theory is employed to combine the advantages of the subjective and objective weighting method, by which the comprehensive weight can be determined. A numerical example is given to demonstrate the proposed modeling process. Through programming drawing images for comparative analysis and sensitivity analysis, study image trends, and draw conclusions, the proposed model effectively alleviates the weight deviation and has higher rationality and extensibility in supplier selection.