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 A branch and bound hybrid algorithm with four deterministic heuristics for the resource constrained project scheduling problem (RCPSP)

DYNA ◽  
2015 ◽  
Vol 82 (190) ◽  
pp. 198-207 ◽  
Author(s):  
Daniel Morillo Torres ◽  
Luis Fernando Moreno Velasquez ◽  
Francisco Javier Díaz Serna
Keyword(s):  
Branch And Bound ◽  
Project Scheduling ◽  
Search Tree ◽  
Feasible Region ◽  
Scheduling Problem ◽  
Optimal Solutions ◽  
Resource Constrained ◽  
Basic Algorithm ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem

This paper addresses the Resource Constrained Project Scheduling Problem (RCPSP). For its solution, a hybrid methodology, which uses a Branch and Bound basic algorithm with dominance rules, is developed and implemented, and is combined with four deterministic heuristics whose objective is to prune the search tree branches, taking into account the iterations available and, at the same time, to minimize the probability of discarding branches that contain optimal solutions. Essentially, these strategies allow the allocation of most iterations to the most promissory regions in an organized manner using only subsets with similar or the same characteristics as those of the optimal solutions at each level of the tree, thus assuring a broad search within the feasible region and, simultaneously, a good exploitation by the selective use of the subsets by level. Finally, the developed algorithm performance is analyzed by solving some of the problems of the PSPLIB test library.

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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