scholarly journals Comparison of Heuristic Priority Rules in the Solution of the Resource-Constrained Project Scheduling Problem

2021 ◽  
Vol 13 (17) ◽  
pp. 9956
Author(s):  
Osman Hürol Türkakın ◽  
David Arditi ◽  
Ekrem Manisalı
Keyword(s):  
Resource Allocation ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Priority Rules ◽  
Resource Constrained ◽  
Start Time ◽  
Project Duration ◽  
Resource Constrained Project Scheduling ◽  
Finish Time ◽  
Positional Weight

Resource-constrained project scheduling (RCPS) aims to minimize project duration under limited resource availabilities. The heuristic methods that are often used to solve the RCPS problem make use of different priority rules. The comparative merits of different priority rules have not been discussed in the literature in sufficient detail. This study is a response to this research gap. It compares 17 heuristic priority rules and seeks the best performing heuristic priority rule. This is the first study ever that compares heuristic priority rules by considering combinations of variations in (1) resource allocation procedures, (2) number of activities, (3) number of resource constraints, and (4) resource supply levels. The objective is to understand the relative merits of heuristic rules used in solving the RCPS problem. The findings indicate that the “minimum late finish time” rule generates the shortest predicted project duration when used in parallel resource allocation, whereas the “minimum late start time”, “minimum late finish time”, and the “highest rank of positional weight 2” rules perform best in serial resource allocation. It was also found that parallel resource allocation is slightly superior to serial resource allocation in most instances.

A Resource Flow Based Branch-and-bound Algorithm to Solve Fuzzy Stochastic Resource-constrained Project Scheduling Problem

2021 ◽  
Author(s):  
Yaghoub Alipouri
Keyword(s):  
Branch And Bound ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Scheduling Problem ◽  
Optimal Solutions ◽  
Resource Constrained ◽  
Start Time ◽  
Resource Flow ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem

Abstract In this paper a resource flow based branch-and-bound procedure is designed to solve the well-known resource constrained project scheduling problem under the mixed uncertainty of fuzziness and randomness (FS-RCPSP). The objective is to minimize the expected makespan of the project subject to precedence and resource constraints. The proposed branch-and-bound can be employed to obtain optimal solutions and also can be truncated in order to find promising near optimal solutions. The depth-first strategy is utilized for constructing the search tree and earliest start time (EST) concept is adopted for selecting a node for further branching while traversing the tree down to the leaves. The performance of developed branch-and-bound is benchmarked against CPLEX and SADESP across an extensive set of 960 problems. The results returned by the proposed algorithm show experimentally its effectiveness to solve the FS-RCPSP.

scholarly journals On some implementations of solving the resource constrained project scheduling problems

2019 ◽  
Vol 29 (1) ◽  
pp. 31-42 ◽  
Author(s):  
E.Kh. Gimadi ◽  
E.N. Goncharov ◽  
D.V. Mishin
Keyword(s):  
Renewable Resources ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Scheduling Problems ◽  
Makespan Minimization ◽  
Resource Constrained ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem ◽  
Technological Constraints

We consider a resource-constrained project scheduling problem with respect to the makespan minimization criterion. The problem accounts for technological constraints of activities precedence together with resource constraints. Activities pre- emptions are not allowed. The problem with renewable resources is NP-hard in the strong sense. We propose an exact branch and bound algorithm for solving the problem with renewable resources. It uses our new branching scheme based on the representation of a schedule in form of the activity list. We use two approaches of constructing the lower bound. We present results of numerical experiments, illustrating the quality of the proposed lower bounds. The test instances are taken from the library of test instances PSPLIB.

scholarly journals Review of conventional metaheuristic techniques for resource-constrained project scheduling problem

2022 ◽  
Vol 7 (2) ◽  
pp. 95-110 ◽  
Author(s):  
Amir Golab ◽  
Ehsan Sedgh Gooya ◽  
Ayman Al Falou ◽  
Mikael Cabon
Keyword(s):  
Genetic Algorithms ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Heuristic Algorithms ◽  
Single Mode ◽  
Scheduling Problem ◽  
Resource Constrained ◽  
Heuristic Solution ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem

This paper is concerned with an overview of the Resource-Constrained Project Scheduling Problem (RCPSP) and the conventional meta-heuristic solution techniques that have attracted the attention of many researchers in the field. Therefore, researchers have developed algorithms and methods to solve the problem. This paper addresses the single-mode RCPSP where the objective is to optimize and minimize the project duration while the quantities of resources are constrained during the project execution. In this problem, resource constraints and precedence relationships between activities are known to be the most important constraints for project scheduling. In this context, the standard RCPSP is presented. Then, the classifications of the collected papers according to the year of publication and the different meta-heuristic approaches applied are presented. Five weighted articles and their meta-heuristic techniques developed for RCPSP are described in detail and their results are summarized in the corresponding tables. In addition, researchers have developed various conventional meta-heuristic algorithms such as genetic algorithms, particle swarm optimization, ant colony optimization, bee colony optimization, simulated annealing, evolutionary algorithms, and so on. It is stated that genetic algorithms are more popular among researchers than other meta-heuristics. For this reason, the various conventional meta-heuristics and their corresponding articles are also presented to give an overview of the conventional meta-heuristic optimizing techniques. Finally, the challenges of the conventional meta-heuristics are explored, which may be helpful for future studies to apply new suitable techniques to solve the Resource-Constrained Project Scheduling Problem (RCPSP).

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