Design of intelligent logistics path planning algorithm for operations research

• Published in: Applied mathematics and nonlinear sciences Vol. 10; no. 1
• Main Author: Liu, Kexia
• Format: Journal Article
• Language: English
• Published: Beirut Sciendo 01.01.2025; De Gruyter Poland
• Subjects: 68W01; Ant colony algorithm; Customer satisfaction; Customers; Intelligent logistics path planning; Logistics; Low cost high customer satisfaction; Objective function; Operations research
• ISSN: 2444-8656; 2444-8656
• DOI: 10.2478/amns-2025-0232

Operations research method (optimization method) is formed in recent decades, which mainly uses mathematical method to study the optimization way and scheme of various systems, and provides the basis of scientific decision-making for decision-makers. This paper takes a distribution center with multiple customer points as the research object, adds the cargo loss function to the objective function, and considers the fixed cost, transportation cost, penalty cost and customer satisfaction, etc., aiming to establish a logistics and transportation path planning problem model with low cost and high customer satisfaction. Subsequently, the basic ant colony algorithm in operations research is improved and applied for the problems of long search time and easy to fall into the defects of local optimum to obtain the optimal planning of intelligent logistics path. The experimental results show that the vehicle scheduling model considering customer satisfaction has exchanged a substantial increase in the overall value of customers by increasing the input of a small amount of cost, and the satisfaction of the high-value VIP-type customers that the enterprise focuses on is as high as more than 90%, whereas most of the low-value customers are limited to the effect of control cost without wasting the resources of the vehicle capacity to make them feel satisfied. Therefore, the enterprise prioritizes the satisfaction of high-value customers with limited resources.