Hybrid meta-heuristic algorithms for the resource constrained multi-project scheduling problem

Uysal, Furkan
The general resource constrained multi-project scheduling problem (RCMPSP) consists of simultaneous scheduling of two or more projects with common resource constraints, while minimizing duration of the projects. Critical Path Method and other scheduling methods do not consider resource conflicts and practically used commercial project management software packages and heuristic methods provide very limited solutions for the solution of the RCMPSP. Considering the practical importance of multi-project scheduling and the fact that resource constraints impact the schedules and costs significantly, achieving an adequate solution to the problem is crucial for the construction sector. In this research, we present a new hybrid algorithm which is based on genetic algorithm, simulated annealing, backward forward improvement heuristics. The performance of the algorithms is compared with the performances of the known heuristic procedures and commonly used software packages using test instances particularly developed for multi-project environment. Effectiveness of the developed algorithm is further improved with the application of parallel computing strategies with a Graphical Processing Unit (GPU). Results revealed that effective resource management is a vital process but it is ignored by practitioners, heuristic methods and current software packages. Proposed algorithm showed significant improvements on the state of the art algorithms. It is also shown that parallel computing strategies with a GPU has high potential for meta-heuristic applications specifically for construction management research area in which there is a significant gap in the GPU research.


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The resource-constrained project scheduling problem (RCPSP) aims to find a schedule of minimum makespan by starting each activity such that resource constraints and precedence constraints are respected. However, as the problem is NP-hard (Non-Deterministic Polynomial-Time Hard) in the strong sense, the performance of exact procedures is limited and can only solve small-sized project networks. In this study a genetic algorithm is proposed for the RCPSP. The proposed genetic algorithm (GA) aims to find near-o...
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Critical path method (CPM) has been commonly used for scheduling of construction projects. However, CPM only considers the relations between the activities, but does not optimize the resource allocation. Resource leveling problem (RLP) concentrates on optimizing resource utilization histograms obtained by Critical Path Method (CPM) without changing the project duration. Resource leveling is crucial for effective use of construction resources particularly, manpower and machinery resources to minimize the pro...
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Resource-constrained project scheduling problem (RCPSP) is a very important optimization problem in construction project management. Despite the importance of the RCPSP in project scheduling and management, commercial project management software provides very limited capabilities for the RCPSP. In this paper, a hybrid strategy based on genetic algorithms, and simulated annealing is presented for the RCPSP. The strategy aims to integrate parallel search ability of genetic algorithms with fine tuning capabili...
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Tokdemir, Onur Behzat; Dikmen Toker, İrem (American Society of Civil Engineers (ASCE), 2019-02-01)
Although the line-of-balance (LOB) method is widely used for the scheduling of repetitive construction projects, there are only a limited number of studies that deal with the issue of how to incorporate uncertainty in repetitive schedules. In this paper, a delay risk assessment method is proposed for projects scheduled by LOB. In the proposed method, a LOB schedule is prepared considering the target rate of delivery, and then risk scenarios are defined considering the sources of uncertainty and vulnerabilit...
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Abbasi Iranagh, Mahdi; Sönmez, Rifat; Department of Civil Engineering (2015)
Despite the importance of resource optimization in construction scheduling, very little success has been achieved in solving the resource leveling problem (RLP) and resource constrained discrete time-cost trade-off problem (RCDTCTP), especially for large-scale projects. The major objective of this thesis is to design and develop new heuristic and meta-heuristic methods to achieve fast and high quality solutions for the large-scale RLP and RCDTCTP. Two different methods are presented in this thesis for the R...
Citation Formats
F. Uysal, “Hybrid meta-heuristic algorithms for the resource constrained multi-project scheduling problem,” Ph.D. - Doctoral Program, Middle East Technical University, 2014.