研发型企业多项目人力资源调度研究——基于蚁群优化的超启发式算法

现阶段,研发型企业的项目处于多项目环境下,为了解决多项目并行时人力资源争夺问题,本文针对该类企业多项目管理中人力资源调度进行优化研究,以考虑项目延期惩罚成本的最小总成本为目标函数,将现实问题抽象建模。基于国内外的研究提出了一种超启发式算法进行求解,该算法将人力资源调度问题分为项目活动分配和人员选择项目活动两个部分,采用蚁群优化作为高层启发式策略搜索低层启发式规则,再进一步根据规则解构造出可行解。最后本研究设计多组仿真实验与启发式规则进行对比,结果表明该算法有较好的搜索性能,为人力资源的调度问题提供了新的解决方案。     

Scheduling Multi-Mode Resource-Constrained Projects Using Heuristic Rules Under Uncertainty Environment

Project scheduling is a key objective of many models and is the proposed method for project planning and management. Project scheduling problems depend on precedence relationships and resource constraints, in addition to some other limitations for achieving a subset of goals. Project scheduling problems are dependent on many limitations, including limitations of precedence relationships, resource constraints, and some other limitations for achieving a subset of goals. Deterministic project scheduling models consider all information about the scheduling problem such as activity durations and precedence relationships information resources available and required, which are known and stable during the implementation process. The concept of deterministic project scheduling conflicts with real situations, in which in many cases, some data on the activity' s durations of the project and the degree of availability of resources change or may have different modes and strategies during the process of project implementation for dealing with multi-mode conditions surrounded by projects and their activity durations. Scheduling the multi-mode resource-constrained project problem is an optimization problem whose minimum project duration subject to the availability of resources is of particular interest to us. We use the multi-mode resource allocation and scheduling model that takes into account the dynamicity features of all parameters, that is, the scheduling process must be flexible to dynamic environment features. In this paper, we propose five priority heuristic rules for scheduling multi-mode resource-constrained projects under dynamicity features for more realistic situations, in which we apply the proposed heuristic rules (PHR) for scheduling multi-mode resource-constrained projects. Five projects are considered test problems for the PHR. The obtained results rendered by these priority rules for the test problems are compared by the results obtained from 10 well-known heuristics rules rendered for the same test problems. The results in many cases of the proposed priority rules are very promising, where they achieve better scheduling dates in many test case problems and the same results for the others. The proposed model is based on the dynamic features for project topography.     

Multi-Project Scheduling: Analysis of Project Performance

Application of heuristic solution procedures to the resource-constrained, multi-project scheduling problem is analyzed under equal and unequal penalties. The performance of ten scheduling rules is categorized with respect to four project summary measures, namely, resource-constrainedness, location of the peak requirements, and problem size. It is shown that the choice of a scheduling rule can be based upon the resource-constrainedness, problem size, and penalty. These results are based on scheduling, in detail, over 3000 multi-project scheduling problems, each containing three projects and from 24 to 66 activities.     

The resource renting problem subject to temporal constraints

We introduce a project scheduling problem subject to temporal constraints where the resource availability costs have to be minimized. As an extension of known project scheduling problems which consider only time-independent costs, this problem includes both time-independent procurement costs and time-dependent renting costs for the resources. Consequently, in addition to projects where all resources are bought, we can deal with projects where resources are rented. Based on the enumeration of a finite set of schedules which is proved to contain an optimal schedule, we develop a depth-first branch-and-bound procedure. Computational experience with a randomly generated test set containing 10800 problem instances is reported.

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Received: December 1, 1999 / Accepted: November 8, 2000     

Managing and modelling general resource transfers in (multi-)project scheduling

Most approaches to multi-project scheduling are based on the assumption that resources can be transferred between projects without any expense in time and cost. As this assumption often is not realistic, we generalise the multi-project scheduling problem (RCMPSP) by additionally including transfer times and cost. To integrate this aspect, in a first step, we develop a framework for considering resource transfers in single- and multi-project environments. It includes managerial approaches to handle resource transfers, a classification of resource transfer types and new roles that resources can take in these transfers. Afterwards, we define the multi-project scheduling problem with transfer times (RCMPPTT) and formulate it in a basic and an extended version as integer linear programmes. Eventually, it is supplemented for the first time by cost considerations and introduced as resource constrained multi-project scheduling problem with transfer times and cost (RCMPSPTTC). Computational experiments compare the presented managerial approaches and prove the necessity of explicitly considering transfer times in project scheduling already during the planning phase. Moreover, the experiments evaluate the presented MIP models and show that specialised solution procedures are vital.     

Scheduling with alternatives: a link between process planning and scheduling

The objective of this research is to develop and evaluate effective, computationally efficient procedures for scheduling jobs in a large-scale manufacturing system involving, for example, over 1000 jobs and over 100 machines. The main performance measure is maximum lateness; and a useful lower bound on maximum lateness is derived from a relaxed scheduling problem in which preemption of jobs is based on the latest finish time of each job at each machine. To construct a production schedule that minimizes maximum lateness, an iterative simulation-based scheduling algorithm operates as follows: (a) job queuing times observed at each machine in the previous simulation iteration are used to compute a refined estimate of the effective due date (slack) for each job at each machine; and (b) in the current simulation iteration, jobs are dispatched at each machine in order of increasing slack. Iterations of the scheduling algorithm terminate when the lower bound on maximum lateness is achieved or the iteration limit is reached. This scheduling algorithm is implemented in Virtual Factory, a Windows-based software package. The performance of Virtual Factory is demonstrated in a suite of randomly generated test problems as well as in a large furniture manufacturing facility. To further reduce maximum lateness, a second scheduling algorithm also incorporates a tabu search procedure that identifies process plans with alternative operations and routings for jobs. This enhancement yields improved schedules that minimize manufacturing costs while satisfying job due dates. An extensive experimental performance evaluation indicates that in a broad range of industrial settings, the second scheduling algorithm can rapidly identify optimal or nearly optimal schedules.     

A Multi-Resource Project Scheduling Algorithm

A heuristic algorithm for scheduling a multi-resource project is described where the objective is to minimize the project cost for any project duration between some specified time range. Input conditions are realistic and include alternative resource combinations (ARCs) for each activity, resource cost functions and hiring and dismissal costs for changes in resource quantities. The algorithm selects that combination of activity ARCs that gives the minimum cost solution for any feasible project duration, and eventually generates the Variable Cost-Time trade-off relationship from which the minimum cost conditions for the project can be found.     

A real option-based supply chain project evaluation and scheduling method

Supply chain departments spend their time managing numerous projects that will improve and maintain their supply chains. Recent literature has most frequently described the content of these projects and their scheduling but neglected to include risk and uncertainty in the expected cost, profits and time durations of these projects. In this article, we have introduced real option valuation (ROV) to supply chain project scheduling as a flexible method to quantify those risks. Our proposed two-step framework links ROV to all relevant constraints of a multi-project set-up by binary fuzzy goal programming. We applied the framework to a real-life case study data of 21 projects that were facing numerous risks and resource constraints. The results show how scheduling performance improved in comparison to methods ignoring risk and uncertainty (e.g. net present value-based scheduling). For validation we conducted hypothesis tests and sensitivity analysis, and provide an in-depth discussion. The findings contribute to research and practice by capturing project-related risks and managerial flexibilities in general and in supply chains in particular.     

A (μ, λ)-coordination mechanism for agent-based multi-project scheduling

A new generic negotiation-based mechanism to coordinate project planning software agents to share resources among projects is described. The mechanism, which takes into account asymmetric information and opportunistic behavior, is concretized for the decentralized resource constrained multi-project scheduling problem, and evaluated on 80 benchmark instances taken from the literature and 60 newly generated instances. Computational tests show that the proposed mechanism comes close to results obtained by central solution methods. For twelve benchmark instances new best solutions could be computed.     

考虑公有与私有资源约束的多项目调度规则对比研究

为了识别出适用于具有公有资源与私有资源约束的多项目调度问题的优先规则,基于标准测试集MPSPLIB进行计算实验,并基于相对偏差指标对比分析25种经典优先规则在最小化最大完工时间、最小化总拖期、最小化加权总拖期3种决策目标下的表现。实验结果表明,优先规则的表现与决策目标、单项目任务数、并行项目数、资源利用系数等因素之间具有显著相关性。在最小化总拖期目标下,尽管大多数规则的表现与现有文献总体一致,但是MAXTWK和MINSLK规则的表现有着显著差异。所得实验结论对于工程实际多项目调度决策具有指导意义。     

基于优先规则的模糊资源受限多项目调度

在分析国内外相关研究现状的基础上,结合资源受限多项目调度问题的特点,针对多项目中各个工序资源参数的不确定性,通过对工程项目工序资源需求量的模糊表示,建立了模糊资源受限多项目调度模型,并运用基于优先规则的启发式算法对所建立的模型进行调度计算,最后通过算例验证模型的有效性和可行性,以实现多项目资源的优化配置。     

Project scheduling with time-varying resource constraints

With industrial projects increasing in complexity and size, determining realizable schedules that efficiently utilize limited resources represents one of the most challenging project management tasks. In this context, the well-known resourceconstrained project scheduling problem has been extensively studied. However, due to its restrictive assumptions, it allows only partial modelling of real-world scheduling problems. Therefore, this paper deals with a generalized version that considers more evolved types of precedence relationships as well as time-varying resource availabilities, e.g. due to maintenance or vacations. For this problem, appropriate heuristic solution methods, based on priority rules and tabu search, are proposed and evaluated concerning their effectiveness.     

A scatter search heuristic for maximising the net present value of a resource-constrained project with fixed activity cash flows

In this paper, we present a meta-heuristic algorithm for the resource-constrained project scheduling problem with discounted cash flows. We assume fixed payments associated with the execution of project activities and develop a heuristic optimisation procedure to maximise the net present value of a project subject to the precedence and renewable resource constraints. We investigate the use of a bi-directional generation scheme and a recursive forward/backward improvement method from literature and embed them in a meta-heuristic scatter search framework. We generate a large dataset of project instances under a controlled design and report detailed computational results. The solutions and project instances can be downloaded from a website in order to facilitate comparison with future research attempts.     

An iterated-local-search heuristic for the resource-constrained weighted earliness-tardiness project scheduling problem

This paper deals with the weighted earliness-tardiness resource-constrained project scheduling problem with minimum and maximum time lags (WET-RCPSP/max). The problem consists of scheduling the activities of a project subject to prescribed resource and temporal constraints such that the total weighted deviation of the activities' completion times from prescribed due dates is minimized. Key applications are planning of just-in-time production and reactive scheduling. For the (approximative) solution of the WET-RCPSP/max, we present a population-based iterated-local-search heuristic. We also report the results of an experimental performance analysis where this heuristic outperformed state-of-the-art methods.     

Resource-Constrained Scheduling of Projects with Variable-Intensity Activities

We consider resource-constrained scheduling of projects including activities whose resource loading is flexible. We propose a model of project-oriented production in which the application rates of the various resources required by an activity are indexed by the performance speed or intensity of the activity. Heuristic algorithms are introduced for the assignment of activity intensities through time in lieu of traditional, fixed-intensity start-time scheduling. On test problems from the literature, the assignment algorithms are shown to outperform even optimal scheduling algorithms for the fixed-intensity case, yet the assignment algorithms are cornputationally practical for scheduling actual, large-scale industrial projects. We also extend the model and the assignment algorithms to admit production-like workflow dependencies and to interface with aggregate models for multi-project planning.     

Column Generation Based Heuristic Algorithm for Multi-Item Scheduling

The column generation algorithm for the multi-item lot-size scheduling problem under resource constraints is examined and improved upon by augmenting simpler heuristic routines in place of the time-consuming Wagner-Whitin dynamic programming routine. The heuristic algorithms thus developed are tested by controlling problem size, setup time, demand variability, and capacity change costs in test problems. The empirical results indicate that the proposed heuristic algorithms reduce CPU time as well as the number of iterations with only a slight loss in optimality.     

The discrete time/resource trade-off problem in project networks: a branch-and-bound approach

In many solution methods for resource-constrained project scheduling, it is assumed that both the duration of each activity and its resource requirements are known and fixed. In real-life projects, however, it often occurs that only one renewable bottleneck resource is available and that the activities have a total work content which indicates how much work (expressed in man-periods) has to be performed. The objective then is to schedule each activity in one of its possible execution modes, subject to the precedence and resource constraints, in order to minimize the project makespan. We present a branch-and-bound procedure and report computational results, obtained using a full factorial experiment on a randomly generated problem set.     

A constraint-based perspective in resource constrained project scheduling

In this study, a new heuristic approach to the resource constrained project scheduling problem is introduced. This approach, which is called local constraint based analysis (LCBA), is more robust than the dispatching rules found in the literature, since it does not depend on an a priori insight as do the dispatching rules. LCBA consists of the application of local essential conditions which respect the current temporal and resource constraints to generate a necessary sequence of activities at a scheduling decision time point in a single-pass parallel scheduling algorithm. LCBA is a time efficient procedure due to the localized aspect with which the activities are handled. Only the activities which are schedulable at the current scheduling time are considered for the application of the essential conditions. LCBA is tested against well-known rules from the literature and some recently developed rules. This testing is done using a set of problems of a special design and also a set of optimally solved problems from a recent benchmark in the literature. It is observed that near optimal time efficient solutions are obtained by LCBA and the procedure's performance is considerably better than that of the dispatching rules.     

Project scheduling with flexible resources: formulation and inequalities

In this paper, we study a variant of the resource-constrained project scheduling problem in which resources are flexible, i.e., each resource has several skills. Each activity in the project may need several resources for each required skill. We present a mixed-integer linear programming formulation for this problem. Several sets of additional inequalities are also proposed. Due to the fact that some of the above-mentioned inequalities require a valid upper bound to the problem, a heuristic procedure is proposed. Computational experience is reported based on randomly generated data, showing that for instances of reasonable size the proposed model enlarged with the additional inequalities can be solved efficiently.     

基于多项目关键链的ETO型企业计划管理方法

在ETO型制造企业计划管理中存在着多项目环境、工期不确定性、项目延迟以及人为因素影响等问题.根据多项目关键链原理,提出了包含以计划模板建立、计划编制、控制三个部分的计划管理流程;每个部分又划分为若干个步骤;针对步骤分别详细设计了具体应用方法.最后构造了以某大型变压器制造企业为背景的3个产品并行的多项目环境,并采用Crystal Ball软件模拟了该环境,评估结果显示优化后产品平均周期时间比优化前缩短了2.7d.