A robust inventory routing policy under inventory inaccuracy and replenishment lead-time

In this paper, we study an inventory routing problem under replenishment lead-time and inventory inaccuracy, which exist extensively in distribution systems for fresh products, but are often ignored in existing research. To solve the problem, a robust inventory routing policy is developed in three steps. At first, we propose the methods of updating the probability of the current net inventory and predicting those in future periods. For each candidate route, we develop a Robust TQL Algorithm to optimize the replenishment time, replenishment quantity and replenishment stage length. Finally, a genetic algorithm-based method is developed to optimize the delivery route.     

An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem

This problem involves optimizing product collection and redistribution from production locations to a set of processing plants over a planning horizon. This horizon consists of several days, and the collection-redistribution is performed on a repeating daily basis. A single routing plan must be prepared for the whole horizon, taking into account the seasonal variations in the supply. We model the problem using a sequence of periods, each corresponding to a season. We propose an adaptive large-neighborhood search with several specifically designed operators and features. The results show the excellent performance of the algorithm in terms of solution quality and computational efficiency.     

Arc routing problems to restore connectivity of a road network

After a disaster, restoring accessibility in the affected area is critical for response operations. We study two arc routing problems for clearing blocked roads. The first problem minimizes the time to reconnect the road network, while the second maximizes the total benefit gained by reconnecting network components within a time limit. For each problem, we develop a mixed integer programming formulation and two versions of a heuristic algorithm. We conduct computational experiments on Istanbul data and instances adapted from the literature. The heuristics achieve near-optimal or optimal solutions quickly in most of the tested instances.     

Models for relief routing: Equity, efficiency and efficacy

In humanitarian relief operations, vehicle routing and supply allocation decisions are critically important. Similar routing and allocation decisions are studied for commercial settings where efficiency, in terms of minimizing cost, is the primary objective. Humanitarian relief is complicated by the presence of multiple objectives beyond minimizing cost. Routing and allocation decisions should result in quick and sufficient distribution of relief supplies, with a focus on equitable service to all aid recipients. However, quantifying such goals can be challenging. In this paper, we define and formulate performance metrics in relief distribution. We focus on efficacy (i.e., the extent to which the goals of quick and sufficient distribution are met) and equity (i.e., the extent to which all recipients receive comparable service). We explore how efficiency, efficacy, and equity influence the structure of vehicle routes and the distribution of resources. We identify trends and routing principles for humanitarian relief based on the analytical properties of the resulting problems and a series of computational tests.     

Benefits of in-vehicle consolidation in less than truckload freight transportation operations

Researchers and public agencies have proposed consolidation policies as an alternative to increase truck payload utilization and mitigate externalities produced by freight transportation. Understanding and enhancing the economic mechanisms that lead to freight consolidation can ease the implementation of these strategies, increase profits for shippers and carriers, and reduce freight-related negative externalities. An important mechanism that has recently been studied for cost reduction in the freight industry is combinatorial auctions. In these auctions, a shipper invites a set of carriers to submit bids for freight lane contracts. Carriers can bid for individual lanes or bundles of them according to their operational characteristics. These bids are constructed considering direct shipments (Truckload operations) and several biding advisory models have been proposed for this purpose. However, there are economies of scale that can be achieved if shipments are consolidated inside vehicles, which have not been explored in the construction of competitive bids. This paper investigates such benefits and provides insights on the competitiveness and challenges associated to the development of consolidated bids (suitable for Less-Than-Truckload operations). Consolidated bids are constructed using a multi-commodity one-to-one pickup-and-delivery vehicle routing problem that is solved using a branch-and-price algorithm. The numerical experiment shows that non-consolidated bids are dominated by consolidated bids, which implies that this type of operation can increase the likelihood of a carrier to win auctioned lanes, while increasing its profits margins over truckload companies (non-consolidated bids), and keeping the reported benefits that combinatorial auctions represent for shippers.     

战术Ad Hoc网络中的QoS路由协议设计与仿真

基于TDMA的战术Ad Hoc网络,提出一种分布式的资源预约机制,其中收/发节点采 用协商的方式预约时隙,邻居节点通过侦听方式获得时隙被预约的信息,然后依托该机制提 出一种QoS路由协议,该协议能够在网络节点之间选择一条满足QoS要求且相对短的路径进行 预约时隙,同时对于网络拓扑变化引起的链路故障也能局部修复。仿真表明该协议具有开销 小和可靠性高等特点,能够提高战术Ad Hoc网络的QoS保障能力。     

基于PSO的信息熵数据融合非均匀分簇路由算法

针对无线传感器网络分簇算法中能量分布不均衡导致的"热区"和簇头负载过重问题,提出了一种基于PSO算法优化簇头选举的非均匀分簇算法。在候选簇头选举和竞争半径计算过程中综合考虑节点动态能量、节点密度和节点距基站距离,将网络进行非均匀分簇,并引入PSO算法进行最终簇头选举。根据节点能量、节点密度和距基站距离确定簇间单跳多跳结合的路由规则,选取代价函数小的节点作为下一跳节点。基于节点信息熵确定融合阈值,进行簇内数据融合剔除冗余数据。仿真结果表明,改进算法的数据传输量比EEUC算法和UCRA算法分别提高了20%和10%,提升了数据的融合效率,有效延长了网络生命周期,簇头能量消耗得到均衡,减少了网络能量消耗,网络的整体性能显著优于其他对比算法。     

无线局域网与无线个域网QoS机制的对比分析

无线局域网(WLAN)和无线个域网(WPAN)技术的发展带来的多媒体业务流量的剧增,使无线网络的资源管理、服务质量(QoS)保障等问题日益突出。传统的媒体访问控制(MAC)协议需要重新设计才能对无线网络的QoS问题进行有效地解决。文中研究了IEEEWLAN和WPAN工作组分别于2002年5月和2003年2月提出的IEEE802.11eD3.0和IEEE802.15.3D16两种协议标准的工作机制并对两者的性能作出了比较分析。     

基于模糊机会约束的物流配送路径优化

在建立基于模糊机会约束的物流配送路径优化问题的数学模型基础上,构造了求解该问题的模糊模拟遗传算法。并用实例验证,结果表明用此算法可以有效的求解此类不确定问题,具有良好的寻优能力。     

时变路网无能力约束车辆路径优化

讨论了一类时变路网下的无能力约束车辆配送路径优化问题,建立了基于时变路网的以配送总耗时最短为优化目标的无能力约束车辆配送路径优化模型。提出了基于实时Dijkstra算法的模型求解方法。数值算例表明考虑路网时变特性得到的优化配送方案将更加符合配送实际。