Journal ArticleDOI
Solving Resource-Constrained Project Scheduling Problem via Genetic Algorithm
TLDR
This paper presents a genetic algorithm (GA) for resource-constrained project scheduling problem (RCPSP) that simplifies and automates the very labor-intensive and therefore time-heavy process of construction management.Abstract:
The resource-constrained project scheduling problem (RCPSP) is an important and challenging problem in the field of construction management. This paper presents a genetic algorithm (GA) for...read more
Citations
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Journal ArticleDOI
Evolving priority rules for resource constrained project scheduling problem with genetic programming
TL;DR: The results show that the hyper-heuristic approach is a viable option when there is a need for a customized scheduling method in a dynamic environment, allowing the automated development of a suitable scheduling heuristic.
Journal ArticleDOI
Linked-Data based Constraint-Checking (LDCC) to support look-ahead planning in construction
Ranjith K. Soman,Ranjith K. Soman,Miguel Molina-Solana,Miguel Molina-Solana,Jennifer Whyte,Jennifer Whyte +5 more
TL;DR: This paper presents a novel method, using semantic web technologies, to model and validate complex scheduling constraints, using the Shapes Constraint Language (SHACL) and demonstrates the potential of LDCC to check for constraint violation in distributed construction data.
Journal ArticleDOI
Scheduling optimization of prefabricated construction projects by genetic algorithm
TL;DR: Research results of the experimental calculation and engineering application show that the proposed project scheduling optimization model and GA are effective and practical, which can help project managers in effectively formulating prefabricated construction project scheduling plans, reasonably allocating resources, reducing completion time, and improving project performance.
Journal ArticleDOI
An Immune Genetic Algorithm for Solving NPV-Based Resource Constrained Project Scheduling Problem
TL;DR: In this paper, a hybrid immune genetic algorithm (IGA) was proposed to solve NPV-based resource constrained project scheduling problem (RCPSP) in many industries, such as construction, software development, and manufacturing.
Posted Content
Scheduling of project networks by job assignment
TL;DR: In this article, a hybrid branch and bound / dynamic programming algorithm with a (rather efficient Monte Carlo type) heuristic upper bounding technique as well as various relaxation procedures for determining lower bounds is presented.
References
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Journal ArticleDOI
A survey of variants and extensions of the resource-constrained project scheduling problem
TL;DR: An overview over various extensions of the basic RCPSP, including popular variants and extensions such as multiple modes, minimal and maximal time lags, and net present value-based objectives, is given.
Journal ArticleDOI
Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation
TL;DR: It is shown that the performance-ranking of priority rules does not differ for single-pass scheduling and sampling, that sampling improves the performance of single- pass scheduling significantly, and that the parallel method cannot be generally considered as superior.
Experimental Investigation of Heuristics for Resource-Constrained Project Scheduling: An Update
Rainer Kolisch,Sönke Hartmann +1 more
TL;DR: In this paper, a survey of heuristics for resource-constrained project scheduling problem (RCPSP) is presented, which provides an update of our survey which was published in 2000.
Journal ArticleDOI
A branch-and-bound procedure for the multiple resource-constrained project scheduling problem
TL;DR: Problems requiring large amounts of computer time using existing approaches for solving this problem type are rapidly solved with the procedure using the dominance rules described, resulting in a significant reduction in the variability in solution times.
Posted Content
Characterization and generation of a general class of resource-constrained project scheduling problems: Easy and hard instances
TL;DR: It is shown that hard instances, being far more smaller in size than presumed in the literature, may not be solved to optimality even within a large amount of computation time.