Development of Optimum Transport Route Design Simulator for Agricultural Products Using GA

利用遗传算法开发农产品最优运输路线设计模拟器

• 批准号: 15580227
• 负责人: SATAKE Takaaki
• 金额: $ 2.3万
• 依托单位: University of Tsukuba
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2003
• 资助国家: 日本
• 起止时间: 2003 至 2004
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15580227/
• 关键词: genetic algorithm; reduction of transport cost; reduction of CO2; design of optimum transport route; simulator; search of transport route; 排出CO_2の削減; 最高輸送経路設計; 輸送経済の探索

The genetic algorithm(GA), which is often used in computer simulation, is a stochastic searching, learning and optimizing method. Utilizing GA, we have developed a basic simulator to find an optimum transport route reducing transport cost of agricultural products. The simulator is coded by ANSI C language. It can find an optimum transport route, given several parameters which are weight of agricultural procedure, passing points, performance of delivery vehicle, etc.Using the software, we have carried out two simulations. The first simulation has been carried out under the condition that the delivery vehicle has no agricultural produce. The second has been done under the condition that the delivery vehicle is not empty. For the sake of comparison, two simulations have also been carried out, utilizing random search algorithm (RS).As a result of simulations, the optimum transport route at an empty run is different from a delivery ; besides the average of fuel costs in the simulation using GA is lower than it using RS. Reduction of the cost has been attained.

通常在计算机模拟中使用的遗传算法（GA）是一种随机搜索，学习和优化方法。利用GA，我们开发了一个基本的模拟器，以找到一条最佳的运输路线，以降低农产品的运输成本。模拟器由ANSI C语言编码。它可以找到一条最佳的运输路线，给定几个参数，这些参数是农业程序的重量，传递点，交付车的性能等。使用软件，我们进行了两个模拟。第一个模拟是在送货车辆没有农产品的条件下进行的。第二个是在运输车辆没有空的条件下完成的。为了进行比较，还使用了随机搜索算法（RS）进行了两个模拟。作为模拟的结果，空运行时的最佳运输路线与交付不同。除了使用GA的模拟中的燃料成本平均外，其燃油成本低于使用Rs。降低成本已经达到。