On the project scheduling problem under stored resource constraints

2002 ◽  
Author(s):  
E.Kh. Gimadi ◽  
S.V. Sevastianov ◽  
V.V. Zalyubovsky
Keyword(s):  
Project Scheduling ◽  
Resource Constraints ◽  
Scheduling Problem ◽  
Project Scheduling Problem

A New Genetic Algorithm for the RCPSP in Large Scale

2013 ◽  
Vol 4 (2) ◽  
pp. 29-40 ◽  
Author(s):  
Hossein Zoulfaghari ◽  
Javad Nematian ◽  
Nader Mahmoudi ◽  
Mehdi Khodabandeh
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Project Scheduling ◽  
Large Scale ◽  
Resource Constraints ◽  
Research Area ◽  
New Method ◽  
Scheduling Problem ◽  
Academic Problem ◽  
Project Scheduling Problem

The Resource Constrained Project Scheduling Problem (RCPSP) is a well-studied academic problem that has been shown to be well suited to optimization via Genetic Algorithms (GA). In this paper, a new method will be designed that would be able to solve RCPSP. This research area is very common in industry especially when a set of activities needs to be finished as soon as possible subject to two sets of constraints, precedence constraints and resource constraints. The presented algorithm in this paper is used to solve large scale RCPSP and improves solutions. Finally, for comparing, results are reported for the most famous classical problems that are taken from PSPLIB.

Resource Constrained Multi-Project Scheduling Problem with Resource Transfer Times

2015 ◽  
Vol 32 (06) ◽  
pp. 1550048 ◽  
Author(s):  
M. Suresh ◽  
Pankaj Dutta ◽  
Karuna Jain
Keyword(s):  
Project Scheduling ◽  
Net Present Value ◽  
Resource Constraints ◽  
Heuristic Approach ◽  
Scheduling Problem ◽  
Priority Rules ◽  
Two Phase ◽  
Resource Transfer ◽  
Project Scheduling Problem ◽  
Transfer Times

Scheduling multi-project is a complex decision making process. It involves the effective and timely allocation of resources to different projects. In the case of multi-project, resources are often transferred between the projects. It consumes both time and cost, when projects are situated in different geographic locations. As a result, the net present value (NPV) of multi-projects is significantly impacted by the resource transfer time. In this paper, a new genetic algorithm (GA) approach to the multi-project scheduling problem with resource transfer times is presented, where the NPV of all projects is maximized subject to renewable resource constraints. The paper also presents a heuristic approach using two phase priority rules for the same problem. We conduct a comprehensive analysis of 60 two-phase priority rules. The proposed GA approach is compared to the heuristic approach using the well-known priority rules. An extensive computational experiment is reported.

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).

Sign in / Sign up

Export Citation Format

Share Document