工程建设企业多项目人力资源配置研究——基于胜任力和两阶段优化视角

主要研究工程建设企业多项目人力资源优化配置问题。以项目经理这一关键性人力资源为对象,构建了基于胜任力模型的工程建设企业项目经理能力定级指标体系,给出了具体的能级评价方法,解决了待分配人员的定级和排序问题;在项目优先级和人员能级界定的基础上,以多项目工期均衡和人工总成本最低为目标建立了两阶段优化模型,给出了基于贪婪算法和线性规划的模型求解算法,设计了MATLAB程序对模型进行求解;最后通过实例验证了优化配置模型和求解算法的有效性。     

双需求集货送货一体化车辆路径问题的数学模型及算法

本文研究了具有总时间和车容量约束的双需求集货送货一体化车辆路径问题,在综合考虑运输费用和车辆出行固定费用的前提下,建立了该问题的整数线性规划模型,并分别给出了求解该模型的精确算法和基于节约准则的启发式算法。最后通过一个具体实例验证了算法的有效性。     

基于区间数的应急物资储备库最小费用选址模型

本文研究了基于区间数的应急物资储备库最小费用选址问题。给出了区间数的概念和运算,构建了参数为区间数的应急物资储备库最小费用选址模型,提出了求模型满意解的算法,最后通过算例分析说明该方法的有效性。     

基于层次分析法和最短路算法的配货模型

本文利用层次分析法,将时间、费用、客户满意度、人力资源等因素结合起来,定量给出了供货商的配货过程中每条线路的权重系数,然后结合最短路算法寻找出运送货物的最优路线．     

具有模糊行程的城市物流动态费用多车型车辆调度问题研究

针对城市物流配送中广泛存在的多车型问题,以及由于交通路况等因素导致的配送行程模糊化现象,给出了一种基于梯形模糊数的,以最小化行程费用为目标的具有模糊行程的动态费用多车型车辆调度问题模型.在问题求解方面,针对基本粒子群算法容易陷入局部最优的情况,引入混沌局部搜索策略,给出了一种基于混沌优化技术的混合粒子群算法.仿真实验表明,该算法具有可行性和有效性.     

钢管的订购和运输解答模型

首先通过最短路算法简化了供需距离网络 ,去掉了铁路、公路等边的性质 ,使供需距离网络简化为一个供需运输价格表 .在此基础上构造了三个模型 :线性费用的网络流模型、改进的线性费用的网络流模型和具有非线性费用的网络流模型 .通过改进传统的最小费用最大流算法 ,解决了本题的非线性费用网络流模型 ,并给出了算法的正确性证明与复杂度分析     

多供应商多零售商下经济批量问题的多项式时间算法研究

基于多供应商和多零售商构成的经济批量问题,通过构建优化模型,分析了订购费用为全部单位数量折扣和增加数量折扣两种情形模型最优解的相关性质。将这些性质应用到动态规划算法设计中,对订购费用为全部单位数量折扣时的一种特殊情形及增加数量折扣的一般情形分别设计了求解问题最优解的多项式时间算法,并用算例说明了算法的执行过程和有效性。     

多部件系统故障预防工作的组合优化

研究了实践中常见的四种预防工作组合类型,即定时维修、功能检测、使用检查及检查与定时维修的组合策略,以单位时间维修费用最小为目标建立了多部件故障预防工作的组合优化模型.在此基础上,提出了两个故障预防工作的组合优化算法,并给出了计算示例以说明模型和算法的性能.     

最小费用最大双流

本文根据一个实例建立了在容量－费用双流网络中求最小费用最大双流的模型，提出了最小费用最大双流和双流增量网络的概念，找出并证明了最小费用双流的充要条件，最后给出该模型的一个算法并估计了算杂性。     

苏浙皖企业家人力资本供给比较研究——基于博弈论与制度演化的视角

在企业持续成长过程中,企业家人力资本供给具有决定性作用。为此,文章基于博弈论与制度演化的视角,对苏浙皖三地企业家人力资本供给做了比较研究,给出国企经理与个私企业家两种不同博弈模型,并论证了相应企业的制度演进及其成长的差异性,最后给出研究结论。     

Hidden heterogeneity in manpower systems: A Markov-switching model approach

In modeling manpower systems, it is of crucial importance to deal with heterogeneity. Until recently, manpower models are dealing with heterogeneity due to observable sources, neglecting heterogeneity due to latent sources. In this paper a two-step procedure is introduced. In the first step personnel groups homogeneous with respect to the transition probabilities are determined in a classical way by taking into account the observable sources of heterogeneity. In the second step heterogeneity caused by latent sources is handled. A multinomial Markov-switching manpower model is introduced that deals with heterogeneity due to latent sources for the internal flows as well as for the wastage flows. The model incorporates the mover-stayer principle. A re-estimation algorithm is presented to estimate the parameters of the Markov-switching manpower model. The switching approach offers a methodology to build a Markov model with personnel groups as states that are more homogeneous, and therefore can contribute to a better validity of the manpower model.     

Short-term manpower planning for MRT carriage maintenance under mixed deterministic and stochastic demands

The purpose of this research is to develop two manpower supply planning models and a solution algorithm for mass rapid transit carriage maintenance under mixed deterministic and stochastic demands. These models are formulated as mixed integer programs that are characterized as NP-hard. We employ problem decomposition techniques, coupled with the CPLEX mathematical programming solver, to develop an algorithm that is capable of efficiently solving the problems. The models and the method used currently in actual operations are evaluated by a simulation-based evaluation method. Finally, we perform a case study using real operating data from a Taiwan MRT maintenance facility. The preliminary results are good, showing that the models could be useful for planning carriage maintenance manpower supply.     

Optimal recruitment strategies in a multi-level manpower planning model

Markov manpower planning models have extensively been analysed in the past in order to find an optimal personnel strategy for which the stocks of the manpower system evolve towards desirable ones. So far, those models do not take into account interactions among different organizational decision levels. In this paper, a multi-level manpower planning model is presented that considers, besides the desirable stock vector at overall level, proposals for the departmental stocks from lower organizational levels. Attainability of the stock vectors at departmental level is examined under control by recruitment and interdepartmental transitions. A multi-level optimization algorithm is presented to determine an optimal recruitment strategy resulting in attainable and acceptable stocks that are a compromise between the proposal from the top and the proposals from the departments.     

Manpower allocation with time windows

In this paper, we propose a manpower allocation model with time windows which is of practical interest. This model originates from a real-life port manpower allocation problem where demand is generated from locations in the yard for servicemen who are dispatched from a central point and where the objectives are to minimize the number of servicemen used, travel distances, travel times and waiting times. We develop a tabu-embedded simulated annealing algorithm and a squeaky wheel optimization with local search algorithm for the problem. Experimental results are reported which show the effectiveness of our approaches.     

Profile‐based push models in manpower planning

A methodology is presented to deal with heterogeneity due to observable variables in modeling personnel systems. For a manpower system, a model based on personnel profiles is introduced. The proposed algorithm concerns an analysis of the evolution of personnel profiles under time‐discrete Markov assumptions. In this way, based on an historical personnel database, the estimation of transition probabilities of profiles as well as the computation of forecasts on the evolution of the manpower system can be found. Based on the presented procedure, a policy supporting software package has been developed for the Belgian Federal Government (research project financed by Federaal Wetenschapsbeleid). Copyright © 2007 John Wiley & Sons, Ltd.     

汽车滚装码头泊位调度优化模型与算法研究

本文研究滚装码头混合泊位分配和劳动力分配的联合调度优化问题。首先,考虑潮汐时间窗约束、装卸劳动力约束、泊位缆桩分布约束以及泊位不规则布局因素,建立以最小化船舶总服务时间为目标的混合整数规划模型。其次,采用内外嵌套算法设计策略,提出求解该类问题的组合算法。其中,外层是多种群并行进化的遗传算法,生成多种船舶计划顺序,内层为基于规则的启发式算法,用于计算给定计划顺序的目标函数值。然后,基于实际运营数据,生成多组不同规模的算例进行全面数值实验,结果表明所提出的算法可在10分钟内求解包含50艘船、100个泊段的算例。最后,开展基于真实滚装码头运营实例的案例分析,对所提模型和算法在实际码头调度问题中的适用性与高效性进行验证。     

A Dynamic Programming Approach to Determine Optimal Manpower Recruitment Policies

The manpower planning models available in the literature have dealt with how changes take place in a manpower planning system, under various operating and policy constraints. However, none of these models has identified the manpower system costs. In this paper we have identified various manpower system costs. Further, we have developed a manpower planning model with the objective of minimizing the manpower system costs. The model has been found to be analogous to the Wagner-Whitin model in production/inventory management. A numerical example has been given to illustrate the model.     

环保意识调查问卷的Logistic模型

本文应用多元统计分析中的方差分析 ,logistic模型等方法对环保意识调查问卷反馈的信息进行统计分析 ,建立被调查企业对环境保护意识的logistic模型 ,进而可对企业家的环境保护意识的好坏进行判断。     

Stochastic multi-site capacity planning of TFT-LCD manufacturing using expected shadow-price based decomposition

This paper presents a stochastic optimization model and efficient decomposition algorithm for multi-site capacity planning under the uncertainty of the TFT-LCD industry. The objective of the stochastic capacity planning is to determine a robust capacity allocation and expansion policy hedged against demand uncertainties because the demand forecasts faced by TFT-LCD manufacturers are usually inaccurate and vary rapidly over time. A two-stage scenario-based stochastic mixed integer programming model that extends the deterministic multi-site capacity planning model proposed by Chen et al. (2010) [1] is developed to discuss the multi-site capacity planning problem in the face of uncertain demands. In addition a three-step methodology is proposed to generate discrete demand scenarios within the stochastic optimization model by approximating the stochastic continuous demand process fitted from the historical data. An expected shadow-price based decomposition, a novel algorithm for the stage decomposition approach, is developed to obtain a near-optimal solution efficiently through iterative procedures and parallel computing. Preliminary computational study shows that the proposed decomposition algorithm successfully addresses the large-scale stochastic capacity planning model in terms of solution quality and computation time. The proposed algorithm also outperforms the plain use of the CPLEX MIP solver as the problem size becomes larger and the number of demand scenarios increases.     

Cost estimation algorithm and decision-making model for curriculum modification in educational organization

The decision about curriculum modification usually takes place at the knowledge level, mainly with consideration of individual academic staff competences and qualifications. However, traditional approaches to cost estimation of curriculum modification are focused on material resources only. In this paper we present a cost estimation method and decision model for curriculum modification in educational organizations. The proposed method works at the knowledge level and employs competence sets as knowledge representation models in educational organizations. Authors used the theory of hierarchical, multilevel systems in order to define the model of the decision-making process of curriculum modification and its dimension. Basing on this and also using a fuzzy competence model the cost estimation algorithm in the form of a group competences expansion algorithm is proposed. The algorithm focuses on the cost of staff competence expansion caused by the knowledge development process.