A solution approach to the inventory routing problem in a three-level distribution system

We consider the infinite horizon inventory routing problem in a three-level distribution system with a vendor, a warehouse and multiple geographically dispersed retailers. In this problem, each retailer faces a demand at a deterministic, retailer-specific rate for a single product. The demand of each retailer is replenished either from the vendor through the warehouse or directly from the vendor. Inventories are kept at both the retailers and the warehouse. The objective is to determine a combined transportation (routing) and inventory strategy minimizing a long-run average system-wide cost while meeting the demand of each retailer without shortage. We present a decomposition solution approach based on a fixed partition policy where the retailers are partitioned into disjoint and collectively exhaustive sets and each set of retailers is served on a separate route. Given a fixed partition, the original problem is decomposed into three sub-problems. Efficient algorithms are developed for the sub-problems by exploring important properties of their optimal solutions. A genetic algorithm is proposed to find a near-optimal fixed partition for the problem. Computational results show the performance of the solution approach.     

Local search for the undirected capacitated arc routing problem with profits

This paper deals with a recently introduced routing problem variant called the undirected capacitated arc routing problem with profits (UCARPP). The UCARPP model considered in the present study is primarily aimed at generating the route set which maximizes the profit collected from a set of potential customers, represented by edges of the examined transportation network. The secondary objective is to minimize the total route travel time. The generated routes are subject both to capacity and travel time constraints. To tackle the examined problem, we propose a local search metaheuristic development which explores two solution neighborhood structures. The conducted search is effectively diversified by means of the promises concept which is based on the aspiration criteria used in tabu search approaches. The proposed algorithm was tested on UCARPP benchmark instances taken from the literature. It efficiently produced high-quality results, improving several previously best known solutions.     

The capacitated general windy routing problem with turn penalties

In this paper we present the capacitated general windy routing problem with turn penalties. This new problem subsumes many important and well-known arc and node routing problems, and it takes into account turn penalties and forbidden turns, which are crucial in many real-life applications, particularly in downtown areas and for large vehicles. We provide a way to solve this problem both optimally and heuristically by transforming it into a generalized vehicle routing problem.     

利用传感器距离和能耗约束的无线传感器网络路由优化

针对大多数现有的无线传感器网络设计方法通常仅找到给定图的最短路径而导致只能优化单个用户性能的问题,提出了一种寻找节点之间的最短路径和最低能耗的路由优化模型,该模型约束WSNs的特定资源,考虑多种约束条件：多周期、最短距离和低能耗。本文按照混合整数线性规划,使用11.0 ILOG CPLEX优化引擎的ILOG OPL开发工具5.5进行编码和求解本文的优化模型。实验结果表明,相比一般可行网络,本文模型的节点的总距离和能耗均有明显降低,此外,在三个不同周期和约束条件数下,每组实验花费的时间均少于10s,完全满足资源有限的无线网络应用要求。     

共享单车再平衡问题及其容差插入启发式算法

共享单车再平衡问题是一类NP-难问题,已有启发式求解算法随着问题规模扩大求解速度显著变慢。本文先讨论了该问题的线路可行变换性质,推导证明了插入构造可行解时,被插入位置允许插入客户点的容量区间。在此基础上,提出容差概念,设计了容差插入启发式算法,对该算法应用标准算例测试表明,算法速度快,参数设置简单;算法找到11个测试算例的当前最好解,其中1个为新的当前最好解;算法求解大容量问题的质量优于中、小容量问题。     

A packet routing strategy using neural networks on scale-free networks

We propose a dynamic packet routing strategy by using neural networks on scale-free networks. In this strategy, in order to determine the nodes to which the packets should be transmitted, we use path lengths to the destinations of the packets, and adjust the connection weights of the neural networks attached to the nodes from local information and the path lengths. The performances of this strategy on scale-free networks which have the same degree distribution and different degree correlations are compared to one another. Our numerical simulations confirm that this routing strategy is more effective than the shortest path based strategy on scale-free networks with any degree correlations and that the performance of our strategy on assortative scale-free networks is better than that on disassortative and uncorrelated scale-free networks.     

开放式多中心需求可拆分VRP及混沌遗传模拟退火算法

综合考虑客户需求量允许被拆分、配送系统拥有多个配送中心且车辆可就近返回配送中心的运输模式,建立以配送中心日均建设成本、车辆派遣成本、理货成本和油耗成本之和最小为目标的数学模型,并根据问题特征设计了混沌遗传模拟退火算法对问题进行求解。通过对不同规模以及不同类型的算例进行实验,验证了混沌遗传模拟退火算法求解本文问题的有效性。     

混合启发式算法求解多配送人员车辆路径问题

为解决带时间窗和多配送人员的车辆路径问题,本文采用混合启发式算法对其进行求解。该算法主要由整数规划重组、局部搜索算法和模拟退火算法三部分组成。在算法中,整数规划重组有效提高了解的质量,局部搜索算法和模拟退火算法保证了算法搜索的深入性和广泛性。通过与CPLEX和禁忌搜索算法进行对比,证实了混合启发式算法实用价值更高,求解效果更好。     

基于一种高生存性RPR网络的路由研究

由标准弹性分组环衍生出的高生存性RPR网络弥补了单环结构中带宽浪费,利用率不高的缺点。基于此多环RPR网络提出了一种路由算法,它将网络中源节点到目的节点的路由过程转换成对相邻节点参考距离的选择,适应了网络的高生存性的特点。通过OPNET完成对路由算法模型的仿真,证明该算法实现了高生存性RPR网络的路由功能,而且具有转发跳数少,路由表结构简单,网络开销小等特点。