Optimization Selection Model and its Genetic Algorithm for a Logistics Chain

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Abstract
There are several paths or nodes to be selected to form a useful and efficient logistics chain. But how to decide which path or node would be selected is an issue in the field of logistics planning and optimization. The issue can be described as mixed-integer programming. And the model can be settled by some exact algorithm, such as the branch and bound method, or random-heuristic search method when the dimensions of the problem are small. But when the dimensions of the problem are large, the problem belongs to NP-complete problem. A genetic algorithm is designed to settle the model. The main impact facts of the algorithm, such as coding, representation of the data, population size, and fitness function, are analyzed.