大规模多设施Weber问题的改进Cooper算法

 多设施Weber问题（multi-source Weber problem,MWP）是设施选址中的重要模型之一,而Cooper算法是求解MWP最为常用的数值方法.Cooper算法包含选址步和分配步,两步交替进行直至达到局部最优解.本文对Cooper算法的选址步和分配步分别引入改进策略,提出改进Cooper算法：选址步中将Weiszfeld算法和adaptive Barzilai-Borwein （ABB）算法结合,提出收敛速度更快的ABB-Weiszfeld算法求解选址子问题;分配步中提出贪婪簇分割策略来处理退化设施,由此进一步提出具有更好性质的贪婪混合策略.数值实验表明本文提出的改进策略有效地提高了Cooper算法的计算效率,改进算法有着更好的数值表现.     

推出冲突避免的机场停机位分配问题

为了科学合理地利用机场停机位资源,克服现有模型对飞机进出机位安全性的考虑不足,研究兼顾运行安全和运行效率的机场停机位分配问题.首先分析了飞机在停机坪中的运行过程,提出以主动避免方式来解除飞机进出机位过程中的冲突,从而将具有潜在冲突的飞机对的机位分配作为约束条件,建立了一类推出冲突避免的停机位分配模型.然后对目标函数和约束条件进行分析和简化,将模型转化为线性模型来求解.算例仿真结果验证了该模型的有效性,表明所提出的主动避免冲突方法是能兼顾运行安全和效率的一种有效方法.     

Flying-V型仓储布局货位分配优化方法研究

Flying-V是一种典型的非传统布局方式,根据其布局方式的特性,针对仓储货位分配优化问题,以货物出入库效率最高和货物存放的重心最低为优化目标,建立了货位分配多目标优化模型,并采用自适应策略的遗传算法(GA),以及粒子群算法(PSO)进行求解。根据货位分配的优化特点,在GA算法的选择、交叉和变异环节均采用自适应策略, 同时采用惯性权重线性递减的方法设计了PSO算法,有效地解决了两种算法收敛速度慢和易“早熟”的问题,提高了算法的寻优性能。为了更好地表现两种优化求解算法的有效性和优越性,结合具体的货位分配实例利用MATLAB软件编程实现。通过对比分析优化结果表明,PSO算法在收敛速度和优化效果方面相比于自适应GA算法更具有优势,更加合适于解决Flying-V型仓储布局货位分配优化问题。     

基于移动机器人的拣选系统货架动态储位分配研究

为了提高基于移动机器人的拣选系统拣货效率,更好地满足客户动态需求和订单时效要求,提出了考虑货架后续需求频次、需求紧迫程度以及拥堵因素的货架动态储位分配策略,构建了最小化货架搬运距离的动态储位分配模型,并设计了启发式算法进行模型求解.首先,基于货架需求紧迫程度,构造贪婪算法生成动态货架储位分配的初始解;然后,基于货架在后续批次订单的需求频次及通道间负载均衡,采用邻域搜索算法进行动态货架储位优化.最后,通过与其他静态和动态储位分配方法对比,验证文章提出的模型和算法的有效性.     

航班登机口分配问题的数学建模

登机口作为机场的重要组成部分,其资源利用率直接影响航班服务的效率.针对不同的优先级建立多目标规划模型对航班进行优化分配,采用贪心算法和禁忌搜索算法,结合登机口类型、航班时间的约束,逐次对最大化分配航班问题、最小化中转旅客最短流程时间问题、最小化旅客总体紧张度问题进行建模求解.结果表明该算法不仅提升了求解速度,并且在航班登机口分配问题中展现了较好的综合寻优能力.这对民航机场实现经济效益、提高旅客满意度有一定的参考价值.     

多因素指派模型全局优化问题研究

基于多因素资源优化分配问题的不确定性,建立基于区间数型下的不确定多因素指派模型,给出模型建立的理论依据与全局优化算法,拓展区间数型多因素指派模型,解决了不确定条件下多因素资源优化分配问题.考虑多因素影响,基于任务完成效率,以5类任务多因素分配问题为例,获得了指派模型全局优化的解.为不确定条件下资源优化分配问题的研究拓宽了决策途径.     

弹性光网络一类调度问题的一个新模型和算法

采用网络功能虚拟化技术的弹性光网络是一种新型的网络,其数据中心的合理部署,路由的科学规划及频谱的最优分配是一个关键而具有挑战的问题.为了解决这个问题,建立了弹性光网络资源分配和任务调度问题一个新的优化模型,新模型以虚拟网络功能在数据中心部署的负载最均衡,经过数据中心节点的路径最短以及频谱占用最少为目标,可同时使虚拟网络功能在数据中心部署,路径规划和频谱分配方案最优.为有效求解该模型,分别设计了一个经过所选数据中心的最短路径策略,虚拟网络功能在数据中心的部署策略以及频谱分配策略,构造了初始种群的产生方法,设计了新的变异算子,在此基础上,提出了求解模型的一个新的进化算法.最后进行了仿真实验,结果表明,最大频隙号和数据中心VNF部署数目的标准差相比对比算法有明显降低,验证了所建模型和算法的有效性.     

人力资源多维分配问题的混合算法

针对已有多维分配问题求解算法复杂、耗时长及精度低等问题,本文将二部图中寻求最优匹配的方法进行推广,运用试分配、饱和路调整和增广路调整对多维分配问题的最优解进行搜索,提出了求解人力资源多维分配问题的最小零面优先分配混合算法和随机试分配混合算法,对算法的有效性进行了理论证明,并分析了算法的时间和空间复杂度;同时通过这两种混合算法对初始零元素数不同的代价矩阵求解时间的计算,以及与Lagrangian松弛算法和剪枝法的耗时、精度的对比,分别得到了两种混合算法的适用性和高效性,最后通过算例验证了算法的有效性。     

弹性需求下城市公交网络服务的优化

对具有弹性需求的城市公交网络系统进行了票价结构与发车频率组合的优化。考虑到公交定价和发车频率会影响乘客需求以及乘客对路径的选择行为,将这一问题描述为一个双层规划问题,上层是寻求社会福利最大的优化问题;下层考虑了乘客的出行选择行为,为弹性需求下乘客在城市公交网络上流量分布的随机用户平衡分配模型。鉴于双层规划问题的非凸性,运用模拟退火算法对模型进行求解,并给出一个仿真算例说明提出的模型和算法的合理性。     

种群规模自适应粒子群在配送中心连续型选址中的应用

本文依照更具有现实意义的“加工厂—配送中心—用户”的模式建立物流配送中心连续型选址模型,并针对较大规模的选址问题提出求解算法。该算法是将具有较强鲁棒性的自适应粒子算法和改进的ALA(Alert Location-Allocation)方法结合而得,该算法中种群规模自适应变化,对经典粒子移动方程进行改进,消除了学习因子,惯性因子随粒子适应值自适应变化,改进的ALA方法提高了算法计算效率。数值试验表明,本文所建模型具有一定的实践优越性,所提出的算法能有效避免陷入局部最优,寻优能力和鲁棒性均较强。     

A heuristic for scheduling in a two-stage hybrid flowshop with renewable resources shared among the stages

In this paper we propose a heuristic for solving the problem of resource constrained preemptive scheduling in the two-stage flowshop with one machine at the first stage and parallel unrelated machines at the second stage, where renewable resources are shared among the stages, so some quantities of the same resource can be used at different stages at the same time. Availability of every resource at any moment is limited and resource requirements of jobs are arbitrary. The objective is minimization of makespan. The problem is NP-hard. The heuristic first sequences jobs on the machine at stage 1 and then solves the preemptive scheduling problem at stage 2. Priority rules which depend on processing times and resource requirements of jobs are proposed for sequencing jobs at stage 1. A column generation algorithm which involves linear programming, a tabu search algorithm and a greedy procedure is proposed to minimize the makespan at stage 2. A lower bound on the optimal makespan in which sharing of the resources between the stages is taken into account is also derived. The performance of the heuristic evaluated experimentally by comparing the solutions to the lower bound is satisfactory.     

考虑多阶段共用平行机特征的拖轮作业模式优化

在对拖轮调度问题进行分析的基础之上,将拖轮调度问题归结为一类具有多阶段共用平行机器特征的多处理器任务调度问题。建立了考虑靠泊与停泊两阶段、考虑切换时间的拖轮调度优化模型,并设计了启发式规则与模拟退火相结合的混合算法(HSA)求解该模型。通过运用所设计算法求解仿真算例,并将其结果与三种基于现行调度规则的调度方案进行比较,验证了模型与算法的高效性。基于此,对不同拖轮数量状态下的调度研究结果显示,拖轮总作业时间与平均单艘拖轮作业时间二者存在着一定的矛盾性;并指出采用拖轮适时返回停泊基地的作业模式,可有效地降低拖轮作业时间,进而提高有限拖轮资源的利用率,实现节能减排、绿色运输。     

A hybrid multi-objective evolutionary algorithm based on NSGA-II for practical scheduling with release times in steel plants

The hot metal is produced from the blast furnaces in the iron plant and should be processed as soon as possible in the subsequent steel plant for energy saving. Therefore, the release times of hot metal have an influence on the scheduling of a steel plant. In this paper, the scheduling problem with release times for steel plants is studied. The production objectives and constraints related to the release times are clarified, and a new multi-objective scheduling model is built. For the solving of the multi-objective optimization, a hybrid multi-objective evolutionary algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) is proposed. In the hybrid multi-objective algorithm, an efficient decoding heuristic (DH) and a non-dominated solution construction method (NSCM) are proposed based on the problem-specific characteristics. During the evolutionary process, individuals with different solutions may have a same chromosome because the NSCM constructs non-dominated solutions just based on the solution found by DH. Therefore, three operations in the original NSGA-II process are modified to avoid identical chromosomes in the evolutionary operations. Computational tests show that the proposed hybrid algorithm based on NSGA-II is feasible and effective for the multi-objective scheduling with release times.     

Dynamic priority rule-based forward-backward heuristic algorithm for resource levelling problem in construction project

Resource levelling aims at minimizing the fluctuation of resource usage, which is accomplished by shifting non-critical activities within their float according to some heuristic rules. Most of these rules adopted a unidirectional scheduling based on a static priority rule. In this paper, we propose a dynamic priority rule-based forward-backward heuristic algorithm (FBHA). The FBHA optimizes resource allocation by shifting non-critical activities within their forward free float (FFF), forward total float (FTF) and backward free float (BFF), successively. A project is divided into several phases during each forward/backward scheduling module. In each phase, the shifting sequence and days of non-critical activities depend on a dynamic priority rule set. The FBHA is integrated into the Microsoft Project 2007 commercial software package to improve the performance of the software and facilitate the project planners. One example is analysed to illustrate the iteration process of the proposed FBHA. Another example with multiple precedence constraints is used to demonstrate the effectiveness of the proposed FBHA in complicated construction projects.     

The Systems Approach to Hospitals

By exploiting the relationship between scheduling and sorting, this paper describes a functional heuristic algorithm for seeking a quick and approximate solution to the n-job, M-machine flowshop scheduling problem under the assumption that all jobs are processed on all machines in the same order and no passing of jobs is permitted. The proposed functional heuristic algorithm can be executed by hand for reasonably large size problems and yields solutions which are closer to optimal solutions than those obtained by Palmer's slope index algorithm.     

随机服务时间下异质患者门诊预约调度优化

考虑随机服务时间与行为特征互不相同的异质患者,建立随机混合整数规划模型对门诊预约调度问题展开研究。首先在给定服务顺序的假设下求解了两个患者的预约调度问题;在此基础上,设计启发式算法对多个患者预约方案和服务顺序同时进行优化。数值结果表明:当患者服务时间为独立同分布的随机变量时,患者预约时间间隔呈现先增加后减少的圆顶形状;当患者服务时间服从不同分布时,通过与样本平均近似方法对比,验证了启发式算法的计算效率和有效性。     

An iterated greedy metaheuristic for the blocking job shop scheduling problem

In this paper we consider a job shop scheduling problem with blocking (BJSS) constraints. Blocking constraints model the absence of buffers (zero buffer), whereas in the traditional job shop scheduling model buffers have infinite capacity. There are two known variants of this problem, namely the blocking job shop scheduling with swap allowed (BWS) and the one with no swap allowed (BNS). This scheduling problem is receiving an increasing interest in the recent literature, and we propose an Iterated Greedy (IG) algorithm to solve both variants of the problem. IG is a metaheuristic based on the repetition of a destruction phase, which removes part of the solution, and a construction phase, in which a new solution is obtained by applying an underlying greedy algorithm starting from the partial solution. A comparison with recent published results shows that the iterated greedy algorithm outperforms other state-of-the-art algorithms on benchmark instances. Moreover it is conceptually easy to implement and has a broad applicability to other constrained scheduling problems.     

需要安装时间的平行多功能机排序问题的启发式算法

考虑需要安装时间的平行多功能机排序问题。在该模型中,每个工件对应机器集合的一个子集,其只能在这个子集中的任一台机器上加工,称这个子集为该工件的加工集合;工件分组,同组工件具有相同的加工时间和加工集合,不同组中的工件在同一台机器上连续加工需要安装时间,目标函数为极小化最大完工时间。对该问题NP-难的一般情况设计启发式算法:首先按照特定的规则将所有工件组都整组地安排到各台机器上,然后通过在各机器间转移工件不断改进当前最大完工时间。通过与下界的比较检验算法的性能,大量的计算实验表明,算法是实用而有效的。     

Scheduling non-professional table-tennis leagues

In this paper we consider a sports league scheduling problem which occurs in planning non-professional table-tennis leagues. The problem consists in finding a schedule for a time-relaxed double round robin tournament where different hard and soft constraints have to be taken into account. We model the problem as an integer linear program and a multi-mode resource-constrained project scheduling problem, respectively. Based on the second model a heuristic solution algorithm is proposed, which proceeds in two stages using local search and genetic algorithms. Computational results show the efficiency of the approaches.     

New heuristics for total tardiness minimization in a flexible flowshop

This paper analyses the total tardiness minimization in a flowshop with multiple processors at each stage. While there is considerable research to minimize the makespan, very little work is reported on minimizing the total tardiness for this problem. This research focuses on heuristic methods that consider this environment as a series of parallel machine problems. New dispatching rules are introduced. One of the proposed rules is able to deal with jobs that will come afterwards and not only the available jobs at the decision time. Dispatching rules are also associated with classical (forward and backward) and new list scheduling algorithms. A special scheduling algorithm able to deal with idle times is proposed. Computational experiments in a set of 4,320 literature instances show that the developed heuristics are competitive and outperforms their classical counterparts.