A survey of variants and extensions of the resource-constrained project scheduling problem <s> Network Representations <s> Abstract The movement to product and process development projects that involve joint ventures among strategic partners, as well as the increasing prevalence of projects within organizations has led to increased implementation of project scheduling methods. It is frequently the case that a capital constraint is placed on a project, thus limiting the number and value of activities that can be scheduled to occur simultaneously. However, the quantity of capital available to schedule activities can increase as additional cash is received as progress payments for completed activities. Since the project manager'so objective is to maximize project Net Present Value (NPV), it is important for the manager to develop a schedule that balances the early receipt of progress payments (which improve NPV and increase the capital balance available), with the delay of particularly large expenditures. Due to the intractability of optimal methods, the use of heuristic methods is required to solve problems of practical size. This paper presents the first test of heuristic methods for solving this problem. We use information from a relaxed optimization-guided model that employs information from the unconstrained NPV-optimal problem in heuristic procedure for solving the capital constrained problem. An experimental design is employed to test the heuristics that includes multiple factor levels for a number of project characteristics, including capital utilization, frequency of progress payments, and project network structure. The results indicate very good relative performance for the optimization-guided procedures as compared to two benchmark heuristics. <s> BIB001 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Network Representations <s> In a given project network, execution of each activity in normal duration requires utilization of certain resources. If faster execution of an activity is desired then additional resources at extra cost would be required. Given a project network, the cost structure for each activity and a planning horizon, the project compression problem is concerned with the determination of optimal schedule (duration) of performing each activity while satisfying given restrictions and minimizing the total cost of project execution. This paper considers the project compression problem with time dependent cost structure for each activity. The planning horizon is divided into several regular time intervals over which the cost structure of an activity may vary. But the cost structure of the activities remains the same (constant) within a time interval. Key events of the project attract penalty for finishing earlier or later than the corresponding target times. The objective is to find an optimal project schedule minimizing the total project cost. We present a mathematical model for this problem, develop some heuristics and an exact branch and bound algorithm. Using simulated problems we provide an insight into the computational performances of heuristics and the branch and bound algorithm. <s> BIB002 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Network Representations <s> There have been many survey papers in the area of project scheduling in recent years. These papers have primarily emphasized modeling and algorithmic contributions for specific classes of project scheduling problems, such as net present value (NPV) maximization and makespan minimization, with and without resource constraints. Paralleling these developments has been the research in the area of project scheduling decision support, with its emphasis on data sets, data generation methods, and so on, that are essential to benchmark, evaluate, and compare the new models, algorithms and heuristic techniques. These investigations have extended the frontiers of research and application in all areas of project scheduling and management. In this paper, we survey the vast literature in this area with a perspective that integrates models, data, and optimal and heuristic algorithms, for the major classes of project scheduling problems. We also include recent surveys that have compared commercial project scheduling systems. Finally, we present an overview of web-based decision support systems and discuss the potential of this technology in enabling and facilitating researchers and practitioners in identifying new areas of inquiry and application. <s> BIB003 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Network Representations <s> This paper concentrates on cost sharing situations which arise when delayed joint projects involve joint delay costs. The problem here is to determine “fair” shares for each of the agents who contribute to the delay of the project such that the total delay cost is cleared. We focus on the evaluation of the responsibility of each agent in delaying the project based on the activity graph representation of the project and then on solving the important problem of the delay cost sharing among the agents involved. Two approaches, both rooted in cooperative game theory methods are presented as possible solutions. In the first approach delay cost sharing rules are introduced which are based on the delay of the project and on the individual delays of the agents who perform activities. This approach is inspired by the bankruptcy and taxation literature and leads to five rules: the (truncated) proportional rule, the (truncated) constrained equal reduction rule and the constrained equal contribution rule. By introducing two coalitional games related to delay cost sharing problems, which we call the pessimistic delay game and the optimistic delay game, also game theoretical solutions as the Shapley value, the nucleolus and the τ-value generate delay cost sharing rules. In the second approach the delays of the relevant paths in the activity graph together with the delay of the project play a role. A two-stage solution is proposed. The first stage can be seen as a game between paths, where the delay cost of the project has to be allocated to the paths. Here serial cost sharing methods play a role. In the second stage the allocated costs of each path are divided proportionally to the individual delays among the activities in the path. Copyright Kluwer Academic Publishers 2002(This abstract was borrowed from another version of this item.) <s> BIB004 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Network Representations <s> Abstract Decisions concerning a project’s expedition, traditionally involved considerations regarding time and cost tradeoff. It was recently suggested that the quality of a project should also be taken into considerations. In this paper, we propose a meta-heuristic solution procedure for the discrete time, cost and quality tradeoff problem. This problem involves the scheduling of project activities in order to minimize the total cost of the project while maximizing the quality of the project and also meeting a given deadline. We apply a so called electromagnetic scatter search to solve this problem. In this process, we initially generate a population of feasible solutions. In so doing, we use frequency memory to well sample the feasible region. A number of these solutions are then selected and improved locally. The improved solutions are then combined to generate new set of solutions. The combination process utilizes attraction–repulsion mechanisms borrowed from the electromagnetism theory. The whole process is stopped when no significant improvement in the set of solutions are observed. The validity of the proposed solution procedure is demonstrated, and its applicability is tested on a randomly generated large and complex problem having 19,900 activities. <s> BIB005
Finally, we briefly address the way the activities are represented within the network. In the RCPSP and many of its extensions, the so-called activity-on-node representation is used, that is, each activity corresponds to a node in the network, while the precedence relations are given by arcs between the nodes. In the literature, also an alternative representation can be found, namely the actvity-on-arc network. There, each activity corresponds to an arc in the network, while the nodes represent events. This representation has been used by, e.g., Achuthan and Hardjawidjaja BIB002 , Brânzei et al. BIB004 , Elmaghraby  , Smith-Daniels et al. BIB001 , and Tareghian and Taheri BIB005 . For a brief discussion of the similarities and differences between both representations, we refer to Kolisch and Padman BIB003 .