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Multimode Resource-Constrained Scheduling and Leveling for Practical-Size Projects
AbstractThis paper aims at providing a fast near-optimum solution to the multimode resource-constrained project scheduling problem (MRCPSP) in large-scale projects, with and without resource-leveling constraints. The MRCPSP problem is known to be nondeterministic polynomial-time hard (NP-hard) and h...
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Published in: | Journal of management in engineering 2015-11, Vol.31 (6) |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | AbstractThis paper aims at providing a fast near-optimum solution to the multimode resource-constrained project scheduling problem (MRCPSP) in large-scale projects, with and without resource-leveling constraints. The MRCPSP problem is known to be nondeterministic polynomial-time hard (NP-hard) and has been solved using various exact, heuristic, and metaheuristic procedures. In this paper, constraint programming (CP) is used as an advanced mathematical optimization technique that suits scheduling problems. The IBM ILOG modeling software and its CPLEX-CP solver engine have been used to develop a CP optimization model for the MRCPSP problem. Unlike many metaheuristic methods in literature, the CP model is fast and provides a near-optimum solution to the MRCPSP for projects with hundreds of activities within minutes. The paper compares the CP results with two case studies from the literature to prove the practicality and usefulness of the CP approach to both researchers and practitioners. One case study was used as the basis for creating larger projects with up to 2,000 activities. The results reported in this paper can be used as a benchmark for other researchers to compare and improve. This research contributes to developing a practical decision support system for resolving real-life constraints in projects. |
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ISSN: | 0742-597X 1943-5479 |
DOI: | 10.1061/(ASCE)ME.1943-5479.0000338 |