带运输时间和自动机的法流水作业排序问题的复杂性

研究目标函数为使最大完工时间达到最小的三台机器情况下的流水作业排序问题,同一工件在某台机器上完工后和在下一台机器上开始加工这段时间内,存在称为运输时间的时间间隔,所有的运输工作均由自动机来完成,自动机在同一时间内最多运输一个工件,文章研究该问题及其特殊情况下的复杂性.     

带运输机的流水车间调度的最优算法

研究带运输时间的流水调度:在该问题中有两台机器A,B和一个运输机V,n个工件,工件需要先在机器A上加工然后在机器B上加工最后被运输机V运往目的地,而且运输机V最初停在机器B旁边.模型的目标是使所有工件都运往目的地的时间最短.文中给出了三种情况下的最优调度算法:i)A,B机器加工工件顺序给定时我们给出了线性时间的最优算法;ii)所有的工件加工时间在机器B上时间相等时我们给出了时间复杂度为O(nlogn)的最优算法;iii)机器B上工件最短加工时间大于等于机器A上工件最长加工时间时给出了时间复杂度为O(n~2)的最优算法.     

费用有限的柔性两机自由作业与流水作业排序问题

研究制造商加工环境为两机自由作业和流水作业柔性排序问题,即工件既可以在制造商两台机器上加工,又可以转包给承包商机器加工.承包商有足够多机器,使得每台机器至多加工一个工件.工件在制造商及承包商机器上所需加工时间及费用均不同.本文需要确定被转包的工件集及未转包工件的加工顺序,在加工及转包总费用不超过给定值的情况下,分别极小...     

机器具有学习效应的供应链排序问题

研究了机器具有学习效应的供应链排序问题.有多个客户分布在不同位置,每个客户都有一定数量的工件需要在一台机器上进行加工.每个客户的工件在机器上加工时具有学习效应,即后面加工的工件实际加工时间是逐渐缩短的.工件生产完后需要运输到相应的客户处,每一批配送需要花费一定的时间和费用.这里研究了供应链排序理论中主要的四个目标函数,分析了这些问题的复杂性,对于一些情况给出了它们的最优算法.     

具有两种运输方式选择的物流排序问题

本文研究了单机环境下,有两种运输方式可供选择的集成生产和运输的排序问题。有多个工件需要在一台机器上进行加工,工件生产完后需要分批运到客户处。有两种运输方式,普通运输和特快运输可供选择。制造商需要安排工件的加工顺序,选择合适的运输方式和出发时间,以极小化相应的时间目标与运输费用的加权和。研究了排序理论中主要的两个目标函数,分析了问题的复杂性,对于这些问题给出了它们的最优算法。     

带批运输的两台同型机排序问题的改进算法

研究带批运输的两台同型机排序问题. 在该问题中,工件在两台同型机上加工,完工的工件由一辆容量为z的车运输到客户. 这里假设工件有不同的物理大小,目标是求一个时间表使得所有工件送达客户且车回到机器所在位置的时间最小,给出了一个(14/9+ε)-近似算法     

目标是最小化最大完工时间带柔性维修时间限制的两台机器排序问题的一个近似算法

本文研究了两台机器带柔性维修时间限制的排序问题,其中第一台机器在固定的时间内必须进行维修,而第二台机器一直可用,目标是最小化所有工件的最大完工时间。工件在加工过程中不允许中断。对于该问题,我们给出了一个性能比为的近似算法,并证明了该性能比是紧的。     

单机带有可拒绝的供应链排序问题

考虑了单机上带有工件拒绝的供应链排序问题.有多个客户分布在不同区域,每个客户都有一定数量的工件需要在一台机器上进行加工.制造商可以拒绝加工一些工件,但要支付相应的拒绝费用.工件生产完后需要运输到相应的客户处,每一批配送需要花费一定的时间和费用.我们研究了排序理论中主要的几个目标函数,构建了单机情况下的具体模型,分析了问题的复杂性,对具体的问题给出了它们的最优算法.     

带两个服务等级的三台机最优在线算法

研究了带服务等级约束的三台平行机在线排序问题.每台机器和每个工件的服务等级为1或者2,工件只能在等级不高于它的机器上加工,即等级为1的工件只能在等级为1的机器上加工,等级为2的工件可在所有机器上加工.每个工件的加工时间为一个单位,目标是极小化所有工件的总完工时间.考虑两种情形:当一台机器等级为1,两台机器等级为2时,给出了竞争比为17/14的最优在线算法;当两台机器等级为1,一台机器等级为2时,给出了竞争比为43/36的最优在线算法.     

具有学习效应的非同类机资源约束排序问题研究

研究具有学习效应和资源约束的非同类平行机排序,即工件的加工时间与所排机器,所排位置和所用资源都有关系.目地是确定每台机器所分配的工件及其排序和所用的资源量,使所有工件的总完工时间和总资源消耗费用的加权和最小.在非同类机的数量给定的情况下,证明了这个问题能够在多项式时间内解决,并给出了一个例子来说明问题是如何求解的.     

考虑码头内外堆场竞争的集装箱堆存定价模型

针对由于集装箱吞吐量增加造成翻箱成本增加与码头堆场拥堵,考虑内外堆场竞争,构建集装箱堆存定价模型,研究内外堆场竞争下的堆存定价决策和货主移箱决策,分析码头堆场操作成本、场外堆场运输成本、货主需求参数和码头堆场收益的内在关系。算例结果表明:一旦过了免费期立即移箱到场外堆场,货主成本最小。随着场外堆场运输成本的增加,码头堆场的堆存定价和箱量增加,提高码头堆场收益。随着码头堆场操作成本降低,码头堆场堆存价格随之下降,但码头堆存箱量增加,提高码头堆场收益。此外降低堆场定价对货主需求的影响参数以及提高运输成本对货主需求的影响系数,有利于提高码头堆场收益。     

Complexity Results for Flow-Shop and Open-Shop Scheduling Problems with Transportation Delays

We consider shop problems with transportation delays where not only the jobs on the machines have to be scheduled, but also transportation of the jobs between the machines has to be taken into account. Jobs consisting of a given number of operations have to be processed on machines in such a way that each machine processes at most one operation at a time and a job is not processed by more than one machine simultaneously. Transportation delays occur if a job changes from one machine to another. The objective is to find a feasible schedule which minimizes some objective function. A survey of known complexity results for flow-shop and open-shop environments is given and some new complexity results are derived.     

Efficient strategies for transporting mobile forces

During a military operation, it may be necessary to move military units quickly and efficiently from one zone at the theatre of operations to another one. This need is prevalent in particular at the earlier stages of an operation when combat units are accumulating at the theatre of operations. Such mobility missions are carried out by specially designed semi-trailers, called transporters, that carry the armoured fighting vehicles (AFVs) of the military unit. In many cases the number of available transporters is smaller than the number of AFVs that are to be carried, thus several tours of the transporters may be needed to transport the entire unit to its destination. In this paper we examine three generic transportation strategies that may apply to such mobility missions: fixed unloading point, variable unloading point and a flexible strategy in which both loading and unloading points may vary from one tour to another. The efficiency of each specific transportation plan, within a given generic strategy, is evaluated with respect to the criterion of minimum accumulation time.     

基于低碳环保因素的“前港后厂”钢铁产成品运输网络优化

中国大部分钢铁企业深居内陆,出口钢材需远距离运输到港口,再通过海运发往世界各地,故建立港口与钢铁企业的合作关系将尤为重要。与铁路、水路运输相比,公路运输单位换算周转量的碳排放量更高。但中国内陆运输多采用公路运输,这将加剧大气污染。本文提出基于“前港后厂”联运的钢铁产成品运输问题,以加强港口与钢铁企业的合作。为降低运营成本和碳排放量,建立以碳排放成本、运输成本、仓储成本及时间窗惩罚成本最小为目标的钢铁产成品运输网络优化模型;并设计融合和声搜索的环形拓扑结构PSO算法进行求解;最后对仓储成本进行灵敏度分析,以探究其对“前港后厂”模式的影响。结果表明,“前港后厂”模式不仅能有效降低运输网络的总成本和碳排放量,且合理的仓储成本更能加强港口和钢铁企业间的紧密性。     

A Stochastic Bottleneck Transportation Problem

In this paper, a stochastic bottleneck transportation problem, which aims at minimizing the transportation time target subject to a chance constraint, is formulated and an algorithm based on a parametric programming approach is developed to solve it. Further, assuming the transportation costs to be deterministic, a trade-off analysis between the transportation time target and the total cost is given. In addition, methods are developed which give the whole spectrum of optimal solutions to the problems mentioned above. The algorithms are illustrated by numerical examples. The computational complexity of the algorithms is also discussed.     

Consolidation of customer orders into truckloads at a large manufacturer

We describe the development and operation of an interactive system based on a mathematical optimisation model which is used by a major US manufacturer to consolidate customer orders into truckloads. Dozens of users employ the system daily for planning delivery of orders from manufacturing plants to customers by truckload carriers, saving numerous hours of the users' time and reducing transportation costs.     

智能制造环境下的备件生产与运输协同调度问题研究

智能制造和即时配送环境下的备件生产与运输协同调度问题是目前国内研究的一大热点,这是因为备件供应链响应速度已成为当前备件制造企业赢得客户的关键因素。为了提高客户满意度,尽可能缩短从客户下达定制化生产订单到订单配送完成的时间,本文建立了以所有客户总等待时间最短为目标的混合整数规划模型和集合覆盖模型,推导了最优解性质,并设计改进的分支定价算法求得最优解。通过将小规模算例结果与CPLEX进行对比,验证了模型和算法的有效性。多组算例测试结果表明,所提出的模型和算法可以有效提升智能制造环境下的备件供应链运作效率。     

A heuristic approach to the multi-period multi-commodity transportation problem

This paper describes an approach to solving a real-world problem which involves the transportation of multiple types of commodities from a number of sources to a number of destinations in discrete time periods, using a capacitated heterogeneous fleet of vehicles. The preliminary objective is to minimize the total number of discrete periods needed to complete the entire operation. The problem is first formulated as a mixed integer programme and its tractability is then greatly improved by reformulating it through backward decomposition into two separate models and solved iteratively. A heuristic approach harnessing specific features of the second approach is developed for solving large size problems to obtain near-optimal solutions within reasonable time. The design of the heuristic also takes into consideration the secondary objectives of minimizing the total vehicle capacity used and minimizing the total capacity of sources needed to satisfy the demands at the destinations. Computational results are provided for a variety of randomly generated problems as well as problems from the literature. The approach described here may be applied to the multi-period transportation of personnel and goods from multiple starting points to multiple destinations in both military and civilian applications.     

A general Hungarian method for the algebraic transportation problem

In this paper the algebraic transportation problem is introduced which covers besides the Hitchcock and the time transportation problem several other types of transportation problems of practical relevance. To solve this algebraic transportation problem admissible transformations are considered and characterized. Thereupon a transformation algorithm is described which is a generalization of the Hungarian method for the classical transportation problem as well as of a threshold method for time transportation problems.     

Dynamic optimization of the operation of single-car elevator systems with destination hall call registration: Part I. Formulation and simulations

The purpose of this two-part study is to investigate the operation problem of single-car elevator systems with destination hall call registration. Destination hall call registration is such a system in which passengers register their destination floors at elevator halls before boarding the car, while in the ordinary systems passengers specify only the directions of their destination floors at elevator halls and register destination floors after boarding the car. In this part of the study, we formulate the operation problem as a dynamic optimization problem and demonstrate by computer simulations that dynamically optimized operation considerably improves the transportation capability compared to conventional selective collective operation. How to solve the dynamic optimization problem is given in the second part of this study.