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.

遗传算法是一种随机搜索、学习和优化方法，常用于计算机仿真。利用遗传算法，我们已经开发了一个基本的模拟器，以找到一个最佳的运输路线，降低运输成本的农产品。该仿真程序采用ANSI C语言编写。它可以找到一个最佳的运输路线，给出几个参数，这是农业程序的重量，通过点，性能的交付车辆等。使用该软件，我们进行了两次模拟。第一个仿真是在运载工具没有农产品的情况下进行的。第二种是在运载工具不空的情况下进行的。为了比较，还进行了两个模拟，利用随机搜索算法（RS），作为模拟的结果，最佳运输路线在空运行和交付不同，而且平均燃料成本在模拟中使用GA低于它使用RS。降低了成本。