Abstract
Abstract To solve the problem of long logistics delivery time in supply chain, a Mixed Integer Non-linear Program (MINLP) model is built by using Mixed Integer nonlinear programming theory. Firstly, the General algebraic modeling system (GAMS) is used to build the model to fully integrate each parameter of logistics transportation, the total distribution time of the supply chain network, the coverage radius of the logistics base, the number of users, the total capacity of the logistics base, the mode of railway and road transportation, the nonlinear programming model is built and solved by DICOPT solver in GAMS. The cost of logistics can be decreased, transportation time can be reduced, and the logistics system's operating efficiency can be increased in the long term with the help of this algorithm. The proper operation of the logistics system is critical in encouraging the supply chain circulation of various industries and has a direct impact on the society's economic development. The optimal logistics distribution plan with 5 logistics bases covered users of 18 and railway capacity of 2. With the same railway capacity and the same total budget, the larger the number of covered users, the greater the total distribution time increases, but the larger the total budget, the growth of the total distribution time slows down significantly. Experiments show that MINLP model can solve the problem of logistics-based layout optimization in nonlinear logistics management.
Highlights
To solve the problem of long logistics delivery time in supply chain, a Mixed Integer Non-linear Program (MINLP) model is built by using Mixed Integer nonlinear programming theory
The General algebraic modeling system (GAMS) is used to build the model to fully integrate each parameter of logistics transportation, the total distribution time of the supply chain network, the coverage radius of the logistics base, the number of users, the total capacity of the logistics base, the mode of railway and road transportation, the nonlinear programming model is built and solved by DICOPT solver in GAMS
The most critical part of the scientific construction of the logistics system is the selection of the distribution center, which directly determines the decision-making of the distribution route
Summary
Abstract: To solve the problem of long logistics delivery time in supply chain, a Mixed Integer Non-linear Program (MINLP) model is built by using Mixed Integer nonlinear programming theory. Experiments show that MINLP model can solve the problem of logistics-based layout optimization in nonlinear logistics management. The optimization of logistics management through nonlinear programming can effectively improve the transportation efficiency of the logistics system and avoid repeated construction, homogeneous competition, inefficient operation, and other long-term problems in the physical industry. On the basis of the previous proposed algorithm and model research results, based on mixed integer nonlinear programming theory, the problem of logistics base layout is solved, through Mixed Integer Non-linear Program (MINLP) model to solve the supply chain network distribution time minimization problem. Through experiments it was observed that, this model can solve a problem of logistics-based layout optimization in nonlinear logistics management
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