A survey of variants and extensions of the resource-constrained project scheduling problem <s> Test Instance Generators <s> Abstract We offer a methodology, and the relevant software, to generate source-terminal directed project nets of specified number of nodes, number of activities, complexity index, and ranges of costs and resources utilization. <s> BIB001 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Test Instance Generators <s> With the development of project scheduling models and methods arose the need for data instances in order to benchmark the solution procedures. Generally, benchmark instances can be distinguished by their origin into real world problems and artificial problems. The analysis of algorithmic performance on real world problem instances is of a high practical relevance, but at the same time it is only an analysis of individual cases. Consequently, general conclusions about the algorithms cannot be drawn. A solution procedure which shows very good performance on one real world instance might produce poor results on another. In order to allow a systematic evaluation of the performance of algorithms, characteristics of the projects have to be identified. The characteristics can then serve as the parameters for the systematic generation of artificial instances. The variation of the levels of these problem parameters in a full factorial design study allows to produce a set of well-balanced instances (cf. Montgomery 1976). <s> BIB002 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Test Instance Generators <s> Abstract Project scheduling has long been an area of intensive research, but until recently most efforts have been dedicated to developing solution procedures and generalizing models, with little work done on generating problem instances. Additionally, if labor time regulations have to be taken into consideration, the classical resource-constrained project scheduling problem (RCPSP) cannot be used for many problems in manpower scheduling. This paper introduces several extensions to the RCPSP aimed at modeling such problems, and a problem instance generator based on the project generator ProGen incorporating these extensions. Thus, it becomes possible to thoroughly test solution procedures for, e.g., audit-staff scheduling, crew scheduling and timetabling problems. Preliminary computational results are given that were obtained with a greedy randomized solution method using priority rules specifically tailored to the generalized model. <s> BIB003 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Test Instance Generators <s> In this paper, we describe RanGen, a random network generator for generating activity-on-the-node networks and accompanying data for different classes of project scheduling problems. The objective is to construct random networks which satisfy preset values of the parameters used to control the hardness of a problem instance. Both parameters which are related to the network topology and resource-related parameters are implemented. The network generator meets the shortcomings of former network generators since it employs a wide range of different parameters which have been shown to serve as possible predictors of the hardness of different project scheduling problems. Some of them have been implemented in former network generators while others have not. <s> BIB004 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Test Instance Generators <s> This paper evaluates and compares different network generators to generate project scheduling problem instances based on indicators measuring the topological network structure. We review six topological network indicators in order to describe the detailed structure of a project network. These indicators were originally developed by [L.V. Tavares, J.A. Ferreira and J.S. Coelho, The risk of delay of a project in terms of the morphology of its network, European Journal of Operational Research 119 (1999), 510–537] and have been modified, or sometimes completely replaced, by alternative indicators to describe the network topology. The contribution of this paper is twofold. Firstly, we generate a large amount of different networks with four project network generators. Our general conclusions are that none of the network generators are able to capture the complete feasible domain of all networks. Additionally, each network generator covers its own network-specific domain and, consequently, contributes to the generation of data sets. Secondly, we perform computational results on the well-known resource-constrained project scheduling problem to prove that our indicators are reliable and have significant, predictive power to serve as complexity indicators. <s> BIB005
When testing exact or heuristic methods for project scheduling, test instances are necessary. In recent years, several parameter-driven instance generators for the RCPSP and many of its extensions have been developed. This section gives a brief overview of the problem variants that have been covered (a discussion of the control parameters is beyond the scope of this work). Kolisch et al.  develop a generator called ProGen for the classical RCPSP as well as the multi-mode extension. It has been applied to generate several sets with test instances for these problem classes. These sets which are comprised in the internet-based library PSPLIB (see Kolisch and Sprecher [112] and Kolisch et al. BIB002 ) have been used in a huge number of studies. ProGen has been extended to cover further extensions of the RCPSP. Schwindt  develops a version called ProGen/max in order to include minimal and maximal time lags. This generator can also produce activities with multiple modes as well as instances for the resource leveling and the resource investment problem. Drexl et al. BIB003 introduce a version called ProGen/πx which incorporates partially renewable resources, mode identity, mode-dependent and sequencedependent setup times (called changeover times here), mode-dependent minimum time lags, and forbidden periods for activities. Agrawal et al. BIB001 suggest a generator called DAGEN for activity-on-arc project networks. Demeulemeester et al. BIB004 develop RanGen, a generator for single-mode and multi-mode project instances which is based on different control parameters than ProGen. Vanhoucke et al. BIB005 provide RanGen2, which extends RanGen by incorporating further topological network measures. Browning and Yassine  propose a generator for problems consisting of multiple projects where the activities are associated with due dates.