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首页> 外文期刊>Expert Systems with Application >Mix-opt: A new route operator for optimal coverage path planning for a fleet in an agricultural environment
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Mix-opt: A new route operator for optimal coverage path planning for a fleet in an agricultural environment

机译:混合选择:一种新的路线运营商,可为农业环境中的车队提供最佳覆盖路径规划

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摘要

To accomplish agriculture tasks, a field is usually divided into tracks based on the implement width. The order in which the crop tracks are covered during this process is critical because it directly affects the distances travelled by the agricultural machines while completing the task and, consequently, soil compaction and inputs. Identifying the best tracks for a set of vehicles to completely cover a field can be formulated as a capacitated vehicle routing problem (CVRP), in which tracks can be viewed as the customers of the CVRP problem. In other words, given a set of n tracks and m vehicles, the objective is to determine a set of routes such that each track is covered exactly once by any of the involved vehicles while minimizing the total cost of covering all the tracks. There are many metaheuristic optimisation methods that address the CVRP problem by using operators to iteratively improve the routes. Most of these operators consist of easy elementary operations such as relocations, swaps or inversions of the order in which customers in the route are visited. In this paper, a new operator, named Mix-opt, is proposed with the aim of accelerating the convergence of metaheuristic optimisation methods and make them less dependent on the operator chosen on routing problems. The proposed operator combines and extends some of the features of the most commonly used route operators by integrating the best-performing elementary operations on which they are based. Further variants of those elementary operations were tested, such as the use of different numbers of elements in the relocations or swaps or reverse orders as well as combining the operations with local searches. The best variants were selected for integration into the proposed operator. Furthermore, Mix-opt was compared against well-established operators by integrating each of them into a Simulated Annealing algorithm and solving well-known CVRP benchmarks and a typical and complex agricultural routing problem. Finally, the proposed operator was applied to be integrated into an agricultural route planner to identify the best routes in some illustrative agricultural problems.
机译:为了完成农业任务,通常会根据机具宽度将一个田地分为几条路。在此过程中覆盖农作物的顺序非常重要,因为它直接影响完成任务时农机行进的距离,进而影响土壤压实和投入。识别一组车辆的最佳轨迹以完全覆盖一个领域,可以用能力受限的车辆路径问题(CVRP)表示,其中轨迹可以视为CVRP问题的客户。换句话说,给定一组n条轨道和m辆车辆,目标是确定一组路线,以使任何一条涉及的车辆恰好覆盖一次每个轨道,同时将覆盖所有轨道的总成本降至最低。有许多元启发式优化方法通过使用运算符来迭代地改进路由来解决CVRP问题。这些操作员大多数由简单的基本操作组成,例如重新定位,交换或倒换路线中的客户的顺序。在本文中,为了加速元启发式优化方法的收敛并减少对路由问题选择的算子的依赖,提出了一种名为Mix-opt的算子。所提出的运算符通过集成它们所基于的最佳性能基本运算,来合并和扩展最常用的路线运算符的某些功能。测试了这些基本操作的其他变体,例如在重定位或交换或反向订单中使用了不同数量的元素,以及将操作与本地搜索结合在一起。选择了最佳变体以集成到建议的操作员中。此外,通过将每个操作员集成到模拟退火算法中,并解决了众所周知的CVRP基准测试和典型而复杂的农业生产路线问题,将其与成熟的操作员进行了比较。最后,将拟议的运营商应用到农业路线规划器中,以识别一些说明性农业问题中的最佳路线。

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