On Dynamical Situations in Vehicle Routing Problems (DSVRP)

F. M. Aderibigbe, K. J. Adebayo
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引用次数: 1

Abstract

This paper discusses the formulation of a stochastic Vehicle Routing Problem (VRP) process, introduced to existing deterministic VRP process, directing all efforts towards the dynamical situations that occur in a typical VRP setting as it applies to everyday real-life situations. It contrasts the dichotomy between static and dynamical situations in VRP, constructs and analyzes the relationship between static and dynamical situations in Vehicle Routing Problems, formulates an expression to describe the dynamical situation in VRP and relates the problem formulation to existing VRP with a view to solving the problem as it applies to real-life situations, a major trend in the business world today. With a view to achieving these, this paper associates the merits of reactivation of route, re-optimization of operation process and projects an anticipatory demand for a dynamical situation in VRP with stochastic requests via three stages: Pre-Decision States, Decisions States and Post-Decision States. First, as a reaction to anticipatory customers’ requests, the current routing plans need to be re-optimized and current customers’ request reactivated. Second, potential future requests need to be anticipated along current decision making since life itself is dynamic. Decisions need to be made in good time. Though, the limited time frame between when a vehicle leaves and returns to the depot often prohibits extensive optimization in both dimensions rather, answer the questions that arise on how to utilize the limited time effectively and judiciously, satisfying both the current and anticipatory customers equally.
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车辆路径问题(DSVRP)中的动态情形
本文讨论了一个随机车辆路径问题(VRP)过程的公式,该过程被引入到现有的确定性VRP过程中,将所有的努力都指向典型VRP设置中发生的动态情况,因为它适用于日常生活中的情况。它对比了VRP中静态和动态情况之间的二分法,构建并分析了车辆路径问题中静态和动力学情况之间的关系,建立了描述VRP中动态情况的表达式,并将问题公式与现有VRP联系起来,以期在实际情况下解决问题,当今商业世界的一大趋势。为了实现这些目标,本文通过决策前状态、决策状态和决策后状态三个阶段,将重新激活路线、重新优化操作过程和预测VRP动态情况的预期需求的优点与随机请求联系起来。首先,作为对预期客户请求的反应,需要重新优化当前路由计划,并重新激活当前客户的请求。其次,由于生活本身是动态的,因此需要在当前的决策过程中预测未来的潜在需求。需要及时做出决定。尽管如此,车辆离开和返回停车场之间的有限时间框架通常会阻碍在两个维度上进行广泛的优化,相反,请回答出现的问题,即如何有效、明智地利用有限的时间,平等地满足当前和预期客户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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