A survey of variants and extensions of the resource-constrained project scheduling problem <s> Further Temporal Constraints <s> Crew or staff scheduling is a complex combinatorial problem. It consists of assigning tasks to persons which have to perform these task and to schedule the performance of the tasks. Railway and airline crew scheduling problems, audit scheduling problems, school and university course scheduling and staff scheduling in hospitals are typical examples of such combinatorial problems. <s> BIB001 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Further Temporal Constraints <s> The resource constrained project scheduling problem (RCPSP) can formulate many scheduling problems including jobshop and flowshop scheduling problems. In this paper, we extend the definition of RCPSP further so that various complicated constraints and objective functions arising in practice can be handled; for example, each activity can be processed in one of the selectable modes, the available amounts of renewable resources may vary depending on the periods, setup activities can be dealt with, and complex objective functions can be handled. Then, we develop a tabu search based heuristic algorithm, which contains elaborations in representing solutions and in constructing neighborhood. Our code was tested for many benchmarks of RCPSP, and also for some problems from real applications. For a number of RCPSP instances, we found better solutions than the best ones found so far. These computational results indicate the effectiveness and usefulness of our approach. <s> BIB002 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Further Temporal Constraints <s> This paper presents a branch-and-cut based exact solution algorithm for scheduling of projects with variable intensity activities connected by feeding precedence constraints the objective being to minimize the violation of resource constraints. Feeding precedence constraints allow some overlap in the execution of the connected activities and capture the flow of material or information between them. New polyhedral results are obtained and computational results are summarized. <s> BIB003 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Further Temporal Constraints <s> Creating a movie shoot schedule is an important part of the movie production process. Even for a small movie project already 50 activities requiring 130 resources such as different actors, director, team, special effects and locations etc. have to be scheduled respecting complex constraints which may be imposed on single resources as well as on every activity. In this paper, we present the movie shoot scheduling problem and formulate a conceptual model. We present a metaheuristic approach for generating operational schedules, outline the modules of the decision support system Schedule This which we have developed and finally we shortly report practical experiences. Our experience from using the DSS in real movie shooting projects shows significant improvements with respect to faster and better scheduling as well as ad hoc re-scheduling. <s> BIB004 </s> A survey of variants and extensions of the resource-constrained project scheduling problem <s> Further Temporal Constraints <s> 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 (RCMPSPTT) 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. Moreover, the experiments evaluate the presented MIP models and show that specialised solution procedures are vital. <s> BIB005
Bartels and Zimmermann  introduce so-called partially ordered destructive relations for projects that consist of engineering and testing activities in the automotive industry. Such a relation between activities i and j implies that either i must be completed before j starts, or these activities must be executed in different modes (i.e., use different resources). This is relevant for the case that activity j destroys a resource (e.g., a test vehicle which would be destroyed in a crash test) that could also be used by activity i which would not destroy the resource. See also Section 4.3 on the resource types used in this problem setting. In a case study on a real-world project, Hartmann  notes that many medical research projects require that certain activities may not finish in the same period. In order to avoid systematic errors, replications of the same experiment (which correspond to activities) are not allowed to end at the same time. Thereby, it is not prescribed which activity shall finish first. It is shown that this type of temporal constraint is, from a mathematical point of view, a special case of time-dependent requests for renewable resources (see Section 2.2). Brucker and Knust BIB001 introduce parallelity constraints which force two activities to be processed in parallel for at least one period. They also discuss the opposite case in which two activities may not be processed in parallel at all. The latter is extended by minimal separating times between two activities which may not be carried out in parallel. Note that a minimal separating time is different from a minimal time lag since the former is not associated with a precedence relation between the activities. Finally, Brucker and Knust BIB001 introduce so-called bounding constraints which require that a set of activities is carried out for at least l and at most u time units within a given set of periods. Kis BIB003 describes so-called feeding precedence constraints. Each precedence relation between two activities i and j is associated with a percentage g i j which indicates that j may not start before g i j percent of i are completed. Moreover, at any point in time the percentage of j that is completed may not be greater than the percentage of i that is completed. Bomsdorf and Derigs BIB004 consider a class of precedence relations where no activity k may be scheduled between two precedence-related activities i and j. Nonobe and Ibaraki BIB002 use a similar concept which adds a dependency on renewable resources. An immediate precedence constraint i ≺≺ r j between activities i and j implies that i must be finished before j is started and that no other activity k that requires resource r is allowed to be started between the completion time of i and the start time of j. Nonobe and Ibaraki BIB002 use this to ensure that no other activity is started between a setup activity and the activity that requires the setup. They also mention that these immediate precedence constraints can be used to enforce equal start times for activities or to enforce that two activities overlap. Krüger and Scholl BIB005 introduce temporal constraints caused by resource transfers. Transferring resource r from the location where activity i is carried out to the location of activity j requires ∆ i jr time units. In an extended formulation, executing a resource transfer may require another resource.