An Exact Algorithm for the Mode Identity Project Scheduling Problem

In this paper we consider the non-preemptive variant of a multi-mode resource constrained project scheduling problem (MRCPSP) with mode identity, in which a set of project activities is partitioned into disjoint subsets while all activities forming one subset have to be processed in the same mode. We present a depth-first branch and bound algorithm for the resource constrained project scheduling problem with mode identity. The proposed algorithm is extended with some bounding rules to reduce the size of branch and bound tree. Finally, some test problems are solved and their computational results are reported

An exact procedure for the resource-constrained weighted earliness-tardiness project scheduling problem.

In this paper we study the resource-constrained project scheduling problem with weighted earliness-tardiness penalty costs. Project activities are assumed to have a known deterministic due date, a unit earliness as well as a unit tardiness penalty cost and constant renewable resource requirements. The objective is to schedule the activities in order to minimize the total weighted earliness-tardiness penalty cost of the project subject to the finish)start precedence constraints and the constant renewable resource availability constraints. With these features the problem becomes highly attractive in just-in -time environments.We introduce e depth-first branch-and-bound algorithm for the unconstrained weighted earliness-tardiness problem to compute lower bounds. The procedure has been coded in Visual C++, version 4.0 under Windows NT and has been validated on a randomly generated problem set.Studies; Scheduling; Costs; Requirements; Just-in-time;

Resource Tardiness Weighted Cost Minimization in Project Scheduling

In this paper, we study a project scheduling problem that is called resource constrained project scheduling problem under minimization of total weighted resource tardiness penalty cost (RCPSP-TWRTPC). In this problem, the project is subject to renewable resources, each renewable resource is available for limited time periods during the project life cycle, and keeping the resource for each extra period results in some tardiness penalty cost. We introduce a branch and bound algorithm to solve the problem exactly and use several bounding, fathoming, and dominance rules in our algorithm to shorten the enumeration process. We point out parameters affecting the RCPSP-TWRTPC degree of difficulty, generate extensive sets of sample instances for the problem, and perform comprehensive experimental analysis using the customized algorithm and also CPLEX solver. We analyze the algorithm behavior with respect to the changes in instances degree of difficulty and compare its performance for different cases with the CPLEX solver. The results reveal algorithm efficiency

Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach

Purpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a new and fast tracking method is proposed to schedule large scale projects which can help project engineers to schedule the project rapidly and with more confidence. Design/methodology/approach: In this article, a forward approach for maximizing net present value (NPV) in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF) is proposed. The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in forward mode. For this purpose, a Genetic Algorithm is applied to solve. Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. Then algorithm is then applied for scheduling a hospital in practice. Originality/value: The method can be used alone or as a macro in Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities after scheduling a project. This can help project engineers to schedule project activities rapidly with more accuracy in practice.Peer Reviewe

Mode-Based versus Activity-Based Search for a Nonredundant Resolution of the Multimode Resource-Constrained Project Scheduling Problem

[EN] This paper addresses an energy-based extension of the Multimode Resource-Constrained Project Scheduling Problem (MRCPSP) called MRCPSP-ENERGY. This extension considers the energy consumption as an additional resource that leads to different execution modes (and durations) of the activities. Consequently, different schedules can be obtained. The objective is to maximize the efficiency of the project, which takes into account the minimization of both makespan and energy consumption. This is a well-known NP-hard problem, such that the application of metaheuristic techniques is necessary to address real-size problems in a reasonable time. This paper shows that the Activity List representation, commonly used in metaheuristics, can lead to obtaining many redundant solutions, that is, solutions that have different representations but are in fact the same. This is a serious disadvantage for a search procedure. We propose a genetic algorithm(GA) for solving the MRCPSP-ENERGY, trying to avoid redundant solutions by focusing the search on the execution modes, by using the Mode List representation. The proposed GA is evaluated on different instances of the PSPLIB-ENERGY library and compared to the results obtained by both exact methods and approximate methods reported in the literature. This library is an extension of the well-known PSPLIB library, which contains MRCPSP-ENERGY test cases.This paper has been partially supported by the Spanish Research Projects TIN2013-46511-C2-1-P and TIN2016-80856-R.Morillo-Torres, D.; Barber, F.; Salido, MA. (2017). Mode-Based versus Activity-Based Search for a Nonredundant Resolution of the Multimode Resource-Constrained Project Scheduling Problem. Mathematical Problems in Engineering. 2017:1-15. https://doi.org/10.1155/2017/4627856S1152017Mouzon, G., Yildirim, M. B., & Twomey, J. (2007). Operational methods for minimization of energy consumption of manufacturing equipment. International Journal of Production Research, 45(18-19), 4247-4271. doi:10.1080/00207540701450013Hartmann, S., & Sprecher, A. (1996). A note on «hierarchical models for multi-project planning and scheduling». European Journal of Operational Research, 94(2), 377-383. doi:10.1016/0377-2217(95)00158-1Christofides, N., Alvarez-Valdes, R., & Tamarit, J. M. (1987). Project scheduling with resource constraints: A branch and bound approach. European Journal of Operational Research, 29(3), 262-273. doi:10.1016/0377-2217(87)90240-2Zhu, G., Bard, J. F., & Yu, G. (2006). A Branch-and-Cut Procedure for the Multimode Resource-Constrained Project-Scheduling Problem. INFORMS Journal on Computing, 18(3), 377-390. doi:10.1287/ijoc.1040.0121Kolisch, R., & Hartmann, S. (1999). Heuristic Algorithms for the Resource-Constrained Project Scheduling Problem: Classification and Computational Analysis. International Series in Operations Research & Management Science, 147-178. doi:10.1007/978-1-4615-5533-9_7Józefowska, J., Mika, M., Różycki, R., Waligóra, G., & Węglarz, J. (2001). Annals of Operations Research, 102(1/4), 137-155. doi:10.1023/a:1010954031930Bouleimen, K., & Lecocq, H. (2003). A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. European Journal of Operational Research, 149(2), 268-281. doi:10.1016/s0377-2217(02)00761-0Alcaraz, J., Maroto, C., & Ruiz, R. (2003). Solving the Multi-Mode Resource-Constrained Project Scheduling Problem with genetic algorithms. Journal of the Operational Research Society, 54(6), 614-626. doi:10.1057/palgrave.jors.2601563Zhang, H., Tam, C. M., & Li, H. (2006). Multimode Project Scheduling Based on Particle Swarm Optimization. Computer-Aided Civil and Infrastructure Engineering, 21(2), 93-103. doi:10.1111/j.1467-8667.2005.00420.xJarboui, B., Damak, N., Siarry, P., & Rebai, A. (2008). A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems. Applied Mathematics and Computation, 195(1), 299-308. doi:10.1016/j.amc.2007.04.096Li, H., & Zhang, H. (2013). Ant colony optimization-based multi-mode scheduling under renewable and nonrenewable resource constraints. Automation in Construction, 35, 431-438. doi:10.1016/j.autcon.2013.05.030Lova, A., Tormos, P., Cervantes, M., & Barber, F. (2009). An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes. International Journal of Production Economics, 117(2), 302-316. doi:10.1016/j.ijpe.2008.11.002Peteghem, V. V., & Vanhoucke, M. (2010). A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem. European Journal of Operational Research, 201(2), 409-418. doi:10.1016/j.ejor.2009.03.034Węglarz, J., Józefowska, J., Mika, M., & Waligóra, G. (2011). Project scheduling with finite or infinite number of activity processing modes – A survey. European Journal of Operational Research, 208(3), 177-205. doi:10.1016/j.ejor.2010.03.037Kolisch, R., & Hartmann, S. (2006). Experimental investigation of heuristics for resource-constrained project scheduling: An update. European Journal of Operational Research, 174(1), 23-37. doi:10.1016/j.ejor.2005.01.065Debels, D., De Reyck, B., Leus, R., & Vanhoucke, M. (2006). A hybrid scatter search/electromagnetism meta-heuristic for project scheduling. European Journal of Operational Research, 169(2), 638-653. doi:10.1016/j.ejor.2004.08.020Paraskevopoulos, D. C., Tarantilis, C. D., & Ioannou, G. (2012). Solving project scheduling problems with resource constraints via an event list-based evolutionary algorithm. Expert Systems with Applications, 39(4), 3983-3994. doi:10.1016/j.eswa.2011.09.062Drexl, A. (1991). Scheduling of Project Networks by Job Assignment. Management Science, 37(12), 1590-1602. doi:10.1287/mnsc.37.12.1590BOCTOR, F. F. (1996). Resource-constrained project scheduling by simulated annealing. International Journal of Production Research, 34(8), 2335-2351. doi:10.1080/0020754960890502

An Exact algorithm to minimize the makespan in project scheduling with scarce resources and feeding precedence relations

In this paper we study an extension of the Resource-Constrained Project Scheduling Problem (RCPSP) with minimum makespan objective by introducing as precedence constraints the so called “Feeding Precedences” (FP). For the RCPSP with FP we propose a new mathematical formulation and a branch and bound algorithm exploiting the latter formulation. The exact algorithm takes advantage also of a lower bound based on a Lagrangian relaxation of the same formulation. A computational experimentation on randomly generated instances and a comparison with the results achieved by a commercial solver, show that the proposed approach is able to behave satisfactorily

Computational experience with a branch-and-bound procedure for the resource-constrained project scheduling problem with generalized precedence relations.

In a previous paper (De Reyck and Herroelen, 1996a), we presented an optimal procedure for the resource-constrained project scheduling problem (RCPSP) with generalised precedence relations (further denoted as RCPSP-GPR) with the objective of minimizing the project makespan. The RCPSP-GPR extends the RCPSP to arbitrary minimal and maximal time lags between the starting and completion times of activities. The procedure is a depth-first branch -and-bound algorithm in which the nodes in the search tree represent the original project network extended with extra precedence relations, which resolve a resource conflict present in the project network of the parent node. Resource conflicts are resolved using the concept of minimal delaying alternatives, i.e. minimal sets of activities which, when delayed, release enough resources to resolve the conflict. Precedence- and resource-based lower bounds as well as dominance rules are used to fathom large portions of the search tree. In this paper we report new computational experience with the algorithm using a new RCPSP-GPR random problem generator developed by Schwindt (1995). A comparison with other computational results reported in the literature is included.Scheduling;

On the multi-mode, multi-skill resource constrained project scheduling problem : computational results

This paper is concerned with an extension of the Resource-Constrained Project Scheduling Problem (RCPSP) which belongs to the class of the optimization scheduling problems with multi-level (or multi-mode) activities. We developed a practical tool, useful to represent multi-mode projects, and to find a solution for the problem on hand – select the best mode for each resource in each activity in order to minimize the total cost, considering the resource cost, a penalty for tardiness and a bonus for early completion. We implemented an adaptation of a filtered beam search (FBS) algorithm to this problem, using the C# programming language. A “filtered beam” search is a heuristic Branch and Bound (BaB) procedure that uses breadth first search but only the top “best” nodes are kept. We give some of the most important solution details and we report on further computational results, by testing the application for different problem sizes

On the multi-mode, multi-skill resource constrained project scheduling problem (MRCPSP-MS)

In this paper we describe an extension of the Resource-Constrained Project Scheduling Problem (RCPSP). A literature review is presented to place our research in its proper context. The problem presented here belongs to the class of the optimization scheduling problems with multi-level (or multi-mode) activities. This means that the activities can be scheduled at different modes, each mode using a different resource level, implying different costs and durations. Each activity must be allocated exactly one unit of each required resource and the resource unit may be used at any of its specified levels. The processing time of an activity is given by the maximum of the durations that would result from a specific allocation of resources. The objective is to find the optimal solution that minimizes the overall project cost, while respecting a delivery date. A penalty is included for tardiness beyond the specified delivery date. We present a formal description of the problem and a mathematical model for it. We also introduce the implementation algorithm for the problem. The implementation was designed using the JAVA language, and the algorithm proposed is based on a branch and bound procedure, using breadth-first search (BFS) project network traversing, among some heuristic rules to filter large subsets of fruitless candidates relative to resource levels combinations.Fundação para a Ciência e a Tecnologia (FCT

A branch-and-bound procedure for the resource-constrained project scheduling problem with generalized precedence relations.

We present an optimal procedure for the resource-constrained project scheduling problem (RCPSP) with generalized precedence relations (further denoted as RCPSP-GPR) with the objective of minimizing the project makespan. The RCPSP-GPR extends the RCPSP to arbitrary minimal and maximal time lags between the starting and completion times of activities. The procedure is a depth-first branch-and-bound algorithm in which the nodes in the search tree represent the original project network extended with extra precedence relations which resolve a resource conflict present in the parent node. Resource conflicts are resolved using the concept of minimal delaying alternatives, i.e. minimal sets of activities which, when delayed, release enough resources to resolve the conflict. Precedence and resource-based lower bounds as well as dominance rules are used to fathom large portions of the search tree. The procedure can be extended to other regular measures of performance by some minor modifications. Even non-regular measures of performance, such as the maximinization of the net present value of the project or resource levelling objectives, can be handled. The procedure has been programmed in Microsoft* Visual C++ for use on a personal computer. Extensive computational experience is obtained.Scheduling;