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首页> 外文期刊>Journal of decision systems >Artificial Immune System-based algorithm for vehicle routing problem with time window constraint for the delivery of agri-fresh produce
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Artificial Immune System-based algorithm for vehicle routing problem with time window constraint for the delivery of agri-fresh produce

机译:基于人工免疫系统的带时间窗约束的农产品自动配送车辆路径问题算法

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摘要

This paper addresses the problem of delivering continuously deteriorating agri-fresh produce from a wholesaler to a number of retailers, within specific time windows. The prime objective is to decide the routes in such a way that the overall cost incurred in transportation, deterioration and penalty is minimised. To model these conflicting objectives a mathematical modelling approach is proposed. The Vehicle Routing Problem with Time Windows (VRPTW) is a Non-deterministic Polynomial-time hard (NP-hard) problem, without considering the business constraints, and becomes computationally prohibitive with the increase in number of retailers. To solve the VRPTW within feasible time limits, Artificial Immune System (AlS)-based solution methodology is proposed. The algorithm is tested on real-life instances generated from Azadpur wholesale market, New Delhi (India). An experiment is performed on the same problems with other algorithms, such as Genetic Algorithm (GA) and Simulated Annealing (SA), to compare the effectiveness and efficiency of the proposed approach. It is found from the quality of solution and rate of convergence that AIS performed better compared to the other applied approaches.
机译:本文解决了在特定的时间范围内将不断恶化的农产品从批发商运送到许多零售商的问题。主要目的是确定路线,以使运输,损坏和罚款所产生的总成本最小。为了对这些冲突的目标进行建模,提出了一种数学建模方法。带时间窗的车辆路径问题(VRPTW)是一个不确定的多项式时间难题(NP-hard)问题,不考虑业务约束,随着零售商数量的增加,计算上变得越来越困难。为了在可行的时间内解决VRPTW问题,提出了一种基于人工免疫系统(AlS)的解决方法。该算法在从印度新德里Azadpur批发市场产生的真实实例中进行了测试。针对与遗传算法(GA)和模拟退火(SA)等其他算法相同的问题进行了实验,以比较该方法的有效性和效率。从解决方案的质量和收敛速度可以发现,与其他应用方法相比,AIS的性能更好。

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