To solve the Logistics Distribution Vehicle Routing Problem(VRP),the Modified Shuffled Frog leaping Algorithm(MSFLA) is advanced.The Greedy Method is applied to solve the VRP with step-by-step answers,which turns VRP into Traveling Salesman Problem(TSP)seeking for route K. Then SFLA was used to offer solution to TSP.But the traditional model of SFLA is not fit for discrete combinatorial optimization problems.So the traditional one is be improved,and the memetic algorithm is brought in.The computational results demonetrate that compared to ant colony optimization ,local search algorithm,genetic algorithm and the hybrid genetic algorithm, SFLA is faster.It has a stronger ability to achieve the most optimistic result,and is easier to be implemented.

Equipment manufacturing involves the integration of multiple technologies and is a complex product system. In the independent innovation of complex product systems, product development is the most important way. Multi-objective cooperative control has been applied to various industries with remarkable results. In this paper, high quality research and development of complex products in equipment manufacturing industry is the main goal. Inspired by the dimensional parameters of the key structures of the product and the structure of the endocrine regulation network, a multi-objective collaborative controller consisting of a speed and position coordinator, a module consisting of a speed and position coordinator, a hormone discriminator, a hormone optimizer, and a controller is designed. The data from the cooperative control study shows that when the controller parameters [3, 1, 2] are used, the velocity parameter is 0.7, the differential parameter is 0.04, and the controller output parameter is 0.8. The force control parameter is 2, the differential parameter is 0.05, and the controller output parameter is 0.7. In the multi-objective cooperative control experiment, the navigator makes a uniform circular or uniform linear motion with [v 1, w 1] T = [0.06,0.09] T . The vector forms r 2 d = [0.4,0.4] T, r 3 d =[−0.1,0.2] T ,. Both the red curve and the blue curve of the follower appear jittered. The experimental curves and control trajectories illustrate that the controller has good control over the vibration and shock phenomena that occur during the position and speed as well as force control of the product. And exhibits good tracking performance. It shows that the multi-objective collaborative controller plays a role in improving the quality of the development of complex products in the equipment manufacturing industry.

In order to improve the manufacturing project management ability, from the perspective of project management ability evaluation, this paper analyzes the manufacturing project management ability combined with big data technology, and constructs the project management ability evaluation model. Moreover, this paper designs a manufacturing project management maturity evaluation model based on fuzzy mathematics. In addition, this paper analyzes manufacturing project management and capability maturity evaluation models and related theories of fuzzy mathematics, and focuses on the management process and knowledge system of manufacturing projects. Through simulation research, it can be known that the evaluation model of manufacturing project management capability based on big data technology proposed in this paper has good practical effects. Moreover, the implementation of effective research and development project management can increase the success rate of research and development, reduce waste of resources, improve innovation capabilities, and ultimately enhance the core competitiveness of the enterprise.