民航值机人员动态排班问题研究

由于机场地服人员的工作时间具有特殊性,人员需求量通常是由航班数量决定的,一天之中的航班量有高峰和低谷时段,因此不同时段的人员需求也不同.目前大多数机场的值机人员排班实行均衡小组排班制度,每个班次人数均衡,导致人员利用效率差.因此本文首先利用排队论对员工需求进行预测,基于均衡小组排班制度的弊端,提出了组内动态排班模型,并利用此模型进行实例验证,最后提出动态调整的措施.对比均衡小组排班和模型排班结果发现,组内动态排班不仅能够方便进行人员管理,而且提高了员工的工时有效率,减少了人力资源的浪费.     

基于动态列生成算法的飞机排班问题研究

飞机排班是航空运输生产计划的重要环节,对航空公司的正常运营和整体效益有着决定性影响;飞机排班通常构建为大规模整数规划问题,是航空运筹学研究的重要课题,构建的模型属于严重退化的NP-Hard问题.在考虑对多种机型的飞机进行排班时,大大增加了问题的复杂性.针对航空公司实际情况,建立多种机型的飞机排班模型;为实现模型的有效求解,提出了基于约束编程的动态列生成算法;即用约束编程快速求解航班连线(航班串)并计算航班串简约成本,动态选择列集并与限制主问题进行迭代.最后,利用国内某航空公司干线航班网络实际数据验证模型和算法的有效性.     

考虑路网可靠性和空间公平性的次优拥挤收费模型

根据随机路网环境下出行者规避风险的路径选择行为,提出了一种考虑路网可靠性和空间公平性的次优拥挤收费双层规划模型。其中,上层模型以具有空间公平性约束条件下最大化路网的社会福利为目标,下层模型是实施拥挤收费条件下考虑行程时间可靠性的弹性需求用户平衡模型。鉴于双层规划模型的复杂性,设计了基于遗传算法和FrankWolfe算法的组合式算法来求解提出的模型。算例结果表明:考虑行程时间可靠性的次优拥挤收费会产生不同于传统次优拥挤收费的平衡流量分布模式,表明出行者的路径选择行为对拥挤收费结果会产生直接影响;此外,算例结果还说明遗传算法对参数设置具有很强的鲁棒性。     

兼顾公平与效率的云计算并行机资源调度研究

研究在云计算中服务资源优化管理背景下,基于时间窗口的非等同并行机服务资源调度问题.为达到最大任务处理数,选取任务延误时间作为目标函数建立数学模型,并利用蚁群算法为模型求解.设计了算法的各项参数,而且进一步探讨了如何将资源分配的公平性引入到算法中来.还通过仿真算例对比了考虑公平性要素前后的调度结果.从结果来看,提出的模型和算法能够较好的用于解决云计算中的并行机资源调度问题,并以较快的收敛速度找到满足约束条件的较优解.     

机组排班的混合集合规划方法研究

机组成本是仅次于燃料成本的第二大直接运营成本,合理的进行机组人员排班对降低航空公司运营成本有着重要意义。然而,机组排班问题是复杂性非常高的组合优化问题,属于NP难题。本文在分析机组排班问题研究进展的基础上,采用混合集合规划方法,综合考虑多种约束,建立了更具有实用性的机组排班优化模型。本文将运筹学理论与业务逻辑相结合,设计了高效的求解策略。利用多组航空公司真实数据对模型进行测试,测试结果表明,模型可以在较短时间内有效求解达到实际应用规模的机组排班问题。     

警力分配问题中的模糊优选动态规划法

根据市区公安分局基层警力的分配问题的特点,将模糊优选理论与动态规划法相结合建立了多维多目标模糊优选动态规划模型,用此模型对警力进行合理分配,以得到最优警力分配方案,为公安决策者在警力分配问题中提供科学的理论依据.     

基于多技能多渠道变成本的物流联络中心排班

物流联络中心的人力成本随着坐席拥有的技能、服务渠道的多少以及服务时段的不同而不同,对人员进行合理班次设计以节省人力成本尤为必要。考虑现实联络中心工作时间的连续与中断、技能组和渠道组的匹配等,提出采用分阶段法优化班次。首先给出不考虑时间中断的坐席的排班模型A,求得排班方案;接下来,在此基础上将中断时间约束加入,建立模型B,求得班次覆盖矩阵;最后加入排班调整约束,建立模型C,对多技能组中各渠道组进行调整,给出最符合实际情况的最优排班调整方案。数值实验结合物流企业实例和各方案的比较,验证了模型的有效性。该方法为联络中心排班提供了新思路,对其它服务行业的排班也具有一定的参考价值。     

托运人联盟下的订单组合及车货调配问题研究

中小型企业的快速发展使得如何有效利用其物流资源、降低其物流成本成为一个亟需解决的问题。本文基于运输联盟的角度,建立了以最小化总成本为优化目标,综合考虑各运输需求时间窗、运输量等因素的车货调度模型。而后,提出了3种时间窗处理策略,设计了粒子群算法对上述模型进行求解,并通过算例对模型和算法的有效性进行了分析。算例结果表明,该模型一方面能够显著降低物流总成本,另一方面可有效节约使用车辆数。因此,本文研究对降低社会物流成本、整合社会物流资源具有一定的理论意义。     

航空公司机组排班计划研究

以中国国际航空公司北京-成都航班为例,提出一种航空公司制定机组排班计划的新方法。首先以机组异地停留时间最短为目标,应用匈牙利算法生成“机组航班串”;然后,应用人员排班方法求得保证机组每周连休两日的条件下完成“机组航班串”飞行任务的最少机组数;最后,对这些机组制定具体的排班计划。应用该方法制定的机组排班计划使得航空公司在保证机组每周连休两日的条件下能够以最少的机组完成航班飞行任务,且机组在异地的停留时间最短。     

呼叫中心坐席人员排班问题优化模型与算法研究

国内呼叫企业在保证每个坐席人员周内当值相同班次情况下,通过灵活安排周内当班日期与班次来制定排班方案。针对该实际排班场景,构建问题整数规划模型。通过对问题数据特征及优化性质分析,以及对班次人力有效满足区段电话服务需求的量化指标表征,分别提出两个构造性启发式算法。使用企业实例数据对模型算法进行计算实验。实验结果显示,整数规划模型适合于求解小规模排班问题最优解,而启发式算法能够以小计算成本获得大规模排班问题优化解。最后讨论保证员工上班规律性的同班次用工制度对企业人力成本控制的影响。     

处理机具有不同开始加工时间的可中断排序问题

本文对处理机具有的不同开始加工时间的可中断排序问题进行讨论，得到下面结论：若处理机具有相同开始加工时间的可中断排序问题存在最优排序算法，则相应的处理机具有不同开始加工时间的可中断排序问题也存在最优排序算法。     

A disjunctive graph model and framework for constructing new train schedules

Train scheduling is a complex and time consuming task of vital importance in many countries. To create completely new train schedules that are more accurate and efficient than permitted by current techniques, a novel “hybrid” job shop approach is proposed and implemented in this paper. Unique characteristics of train scheduling are firstly incorporated into a disjunctive graph representation of the solution. Dedicated “stand-alone” constructive algorithms that utilise this representation are then developed. The modelling approach and the constructive algorithms are essential as they provide the basis for which meta-heuristics and other iterative refinement algorithms can be applied. A numerical investigation and case study is provided and demonstrates the viability of the modelling approach. Furthermore it is demonstrated that good quality solutions are provided with reasonable computational effort.     

排序、经典排序和新型排序

本文简略地介绍排序,经典排序和新型排序．     

List scheduling algorithms to minimize the makespan on identical parallel machines

In this paper we present constructive algorithms for the classical deterministic scheduling problem of minimizing the makespan on identical machines. Since the problem is known to beNP-hard in the strong sense, the approximate algorithms play a relevant role when solving this problem. The proposed algorithms are based on list scheduling procedures, but the assignment rule is not the same for the full set of jobs. Computational results show that these algorithms perform very well. This research has been partially supported by the Research Project H015/2000, Universidad de Alcalá. The authors are indebted to Joaquín Pérez and the referees for their helpful remarks and comments. We also wish to thank Paul Alexander Ayres for his help in the correct use of English.     

Cyclical scheduling and multi-shift scheduling: Complexity and approximation algorithms

We consider the multiple shift scheduling problem modelled as a covering problem. Such problems are characterized by a constraint matrix that has, in every column, blocks of consecutive 1s, each corresponding to a shift. We focus on three types of shift scheduling problems classified according to the column structure in the constraint matrix: columns of consecutive 1s, columns of cyclical 1s, and columns of k consecutive blocks. In particular, the complexity of the cyclical scheduling problem, where the matrix satisfies the property of cyclical 1s in each column, was noted recently by Hochbaum and Tucker to be open. They further showed that the unit demand case is polynomially solvable. Here we extend this result to the uniform requirements case, and provide a 2-approximation algorithm for the non-uniform case. We also establish that the cyclical scheduling problem’s complexity is equivalent to that of the exact matching problem—a problem the complexity status of which is known to be randomized polynomial (RP). We then investigate the three types of shift scheduling problems and show that, while the consecutive ones version is polynomial and the k-block columns version is NP-hard (for k≥2), for the k-blocks problem we give a simple k-approximation algorithm, which is the first approximation algorithm determined for the problem.     

一种改进的多模式项目反应性调度问题

既有的项目反应性调度问题只关注了基准调度方案的稳定性,而忽略了项目调度目标的最优实现。本文提出了一种两阶段多模式资源受限项目反应性调度问题。第一阶段,在新的项目执行环境下,对项目进行完全重调度,得到新的最优调度目标值。第二阶段,以新的最优调度目标值为约束,以最大化调度稳定性为目标,求得新的最优调度方案。针对问题特点,基于IBM ILOG优化编程语言OPL和CPLEX V12.8.0,设计出该问题的求解程序。最后,基于标准算例,对本文提出的反应性调度方法、既有的反应性调度方法、完全重调度方法进行了充分的比较测试,结果表明本文提出的反应性调度方法在缩短项目工期、保护基准方案的稳定性方面具有明显优势。     

问题1｜pmtn,dj｜hmax的一个最优算法

给出并证明了求解问题１｜ｐｍｔｎ，ｄｊ｜ｈｍａｘ的一个最优算法。     

V-shop scheduling

This paper deals with V-shop scheduling where the route by which a job passes through the machines is: M₁ → M₂ → ? → M_m?1 → M_m → M_m?1 → ? → M₂ → M₁. Flowshop scheduling is a special case of V-shop. The two-machine, minimum schedule length V-shop scheduling problem is proved to be binary NP-complete. Efficient solvable algorithms are presented for some simple special cases of NP-complete V-shop problems; specifically n/2/V/C_max with a dominating machine and n/m/V, t_ij = 1/(C_max ∩ ΣC_i). n/m/V/C_max, m?2, with an increasing series of dominating machines is discussed.     

Learning heuristics for basic block instruction scheduling

Instruction scheduling is an important step for improving the performance of object code produced by a compiler. A fundamental problem that arises in instruction scheduling is to find a minimum length schedule for a basic block—a straight-line sequence of code with a single entry point and a single exit point—subject to precedence, latency, and resource constraints. Solving the problem exactly is known to be difficult, and most compilers use a greedy list scheduling algorithm coupled with a heuristic. The heuristic is usually hand-crafted, a potentially time-consuming process. In contrast, we present a study on automatically learning good heuristics using techniques from machine learning. In our study, a recently proposed optimal basic block scheduler was used to generate the machine learning training data. A decision tree learning algorithm was then used to induce a simple heuristic from the training data. The automatically constructed decision tree heuristic was compared against a popular critical-path heuristic on the SPEC 2000 benchmarks. On this benchmark suite, the decision tree heuristic reduced the number of basic blocks that were not optimally scheduled by up to 55% compared to the critical-path heuristic, and gave improved performance guarantees in terms of the worst-case factor from optimality.     

A Relation between Multiprocessor Scheduling and Linear Programming

The general non preemptive multiprocessor scheduling problem (NPMS) is NP-Complete, while in many specific cases, the same problem is Time-polynomial. A first connection between PMS and linear programming was established by Yannanakis, Sauer and Stone, who associated to any PMS instance some specific linear program. The main result inside this paper consists in a characterization of the partially ordered structures which allow the optimal values of any associated PMS instance to be equal to the optimal values of the corresponding linear programs.