The distribution route selection of chain convenience stores is related to the operation cost and stability of convenience stores, so chain convenience stores need to optimize the distribution route. The improvement of genetic algorithm in the process can provide necessary help, so this paper will carry out research. The research mainly introduces the basic concept of genetic algorithm, and puts forward improvement measures for the classical algorithm, and then uses the improved genetic algorithm to put forward the convenience store distribution path optimization method. Through the research, the improved genetic algorithm has more advantages than the classical algorithm, and can better help the convenience store chain to optimize the distribution path. It can be applied to the practical application of distribution route optimization of convenience store chain enterprises, and help convenience store chain enterprises to improve economic benefits. 

Distribution Route Optimization Method of Chain Convenience Store Based on Improved Genetic Algorithm

The integration of all walks of life and Internet technology has promoted the comprehensive reform of smart city system, and it has become a new expectation to solve a large number of domestic wastes generated by cities. As a result, a waste recycling platform based on Internet technology is required. The overall framework design and functional module design of the platform are investigated in this paper. The overall framework uses a B/S structure, which reduces the system's communication overhead and allows it to take full advantage of the advantages of both hardware environments. The vehicle monitoring module makes use of Beidou positioning to provide hardware services, and the SDK provided by Baidu Map to achieve real-time monitoring; the statistics module makes use of visualization technology, making it easy for managers to check operation details. The path planning module employs genetic algorithms to determine the shortest path. The platform will greatly improve waste recycling efficiency and save more than 40% in labor and time costs.

Research on waste recycling platform Based on internet plus Model: Genetic algorithm planning path

Conventional intelligent layout algorithm of ceramic design drawing elements mainly uses density distribution method to obtain ceramic design drawing element units, which is vulnerable to the influence of pattern density, resulting in a low distribution balance of design drawing elements. Therefore, a new intelligent layout algorithm for ceramic design drawing elements needs to be designed based on a genetic algorithm. That is, combining the characteristics of ceramic design drawing elements, the intelligent parting structure of ceramic design drawing elements is constructed, and then the brilliant layout model of ceramic design drawing elements is designed using genetic algorithm. The experimental results show that the developed intelligent layout algorithm of ceramic design elements has a high distribution balance, which proves that the designed intelligent layout algorithm of ceramic design elements has good performance, reliability, and certain application value, and has made specific contributions to improving the aesthetic quality of ceramic design drawings.

Intelligent Element Layout Algorithm of Ceramic Design Drawing Based on Genetic Algorithm

In recent years, the rapid expansion of urban distribution business and the increase use of traditional fuel logistics trucks have resulted in a lot of environmental, traffic and resource problems. "Green logistics" has become the direction of urban distribution transformation, and replacing fuel vehicles with pure electric logistics vehicles has become a way to meet the requirements of urban end distribution. In this paper, the characteristics of electric logistics vehicles are combined with the constraints of cargo capacity to meet the demand for sufficient power and driving range in the distribution process. Charging operations are carried out using charging piles at fixed locations when necessary, and the time windows of customers at each node are considered and penalty factors are set so that the distribution path of electric logistics vehicles can be well planned, which makes the total logistics cost lowest.

Planning of Vehicle Routing with Mixed Time Windows Based on the Improved Genetic Algorithm (IGA)

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Planning of Vehicle Routing with Mixed Time Windows Based on the Improved Genetic Algorithm (IGA)