Design And Implementation Of Logistics Stowage System Based On Improved Genetic Algorihm

With the rapid development of world economy, there is growing demand for high efficiency and low cost in logistics industry. Traditional mode of the logistics industry management cannot satisfy the intensive market competition. As one of the most representative problem in logistics industry, the solution to the logistics stowage problem can hardly be optimized because of the massive constraints and the big scale of cargoes. Solutions to such problems with heuristics are usually subjected to the mode and algorithms used.In this paper, we run into the demand of commodity logistics with detailed description and analysis. And propose multiple constraints to the load distribution and driving paths design. We also normalize the load distribution and driving paths design to rebuild the logistics stowage problem, improve the searching efficiency and quality of the solutions by transforming the feasible solutions to the genetic algorithm. The experiments for the improved genetic algorithm prove our algorithm’s feasibility and efficiency. We also build an application system based on our algorithm which can efficiently balance the logistics stowage of “labor, vehicle, and cargoes”, and realize the informational, automatic, and formalized management in logistics industry.With the realization of the system function, the logistics industry no longer relies on the traditional manual mode, but in a flexible and automatic mode. Our system can improve the entire running efficiency of the logistics industry management, optimize the shipment and the driving distance to give support to the overall resource control, and finally control the running cost.