A Hybrid Algorithm for a Class of Resource Constrained Scheduling Problems

2005 ◽  
pp. 110-124 ◽  
Author(s):  
Yingyi Chu ◽  
Quanshi Xia
Keyword(s):  
Hybrid Algorithm ◽  
Scheduling Problems ◽  
Resource Constrained

A novel algorithm for solving resource-constrained project scheduling problems: a case study

2019 ◽  
Vol 16 (2) ◽  
pp. 194-215 ◽  
Author(s):  
Mahmood Kasravi ◽  
Amin Mahmoudi ◽  
Mohammad Reza Feylizadeh
Keyword(s):  
Project Scheduling ◽  
Hybrid Algorithm ◽  
Pso Algorithm ◽  
Project Planning ◽  
Heuristic Methods ◽  
Scheduling Problems ◽  
Resource Constrained ◽  
Content Type ◽  
Resource Constrained Project Scheduling

PurposeConstruction projects managers try their best for the project to go according to the plans. They always attempt to complete the projects on time and consistent with the predetermined budgets. Amid so many problems in project planning, the most critical and well-known problem is the Resource-Constrained Project Scheduling Problem (RCPSP). The purpose of this paper is to solve RCPSP using hybrid algorithm ICA/PSO.Design/methodology/approachDue to the existence of various forms for scheduling the problem and also the diversity of constraints and objective functions, myriad of research studies have been conducted in this realm of study. Since most of these problems are NP-hard ones, heuristic and meta-heuristic methods are used for solving these problems. In this research, a novel hybrid method which is composed of meta-heuristic methods of particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) has been used to solve RCPSP. Finally, a railway project has been examined for RCPS Problem in a real-world situation.FindingsAccording to the results of the case study, ICA/PSO algorithm has better results than ICAs and PSO individually.Practical implicationsICA/PSO algorithm could be used for solving problems in a multi-mode situation of activities or considering more constraints on the resources, such as the existence of non-renewable resources and renewable. Based on the case study in construction project, ICA/PSO algorithm has a better solution than PSO and ICA.Originality/valueIn this study, by combining PSO and ICA algorithms and creating a new hybrid algorithm, better solutions have been achieved in RCPSP. In order to validate the method, standard problems available in PSPLib library were used.

‘PLATE’: A decision support system for resource constrained scheduling problems

1994 ◽  
Vol 79 (2) ◽  
pp. 158-166 ◽  
Author(s):  
A.T.M. Aerts ◽  
A. Jansen ◽  
L. Klieb ◽  
C. Noorlander ◽  
G. Wolf
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Scheduling Problems ◽  
Resource Constrained

scholarly journals Integrating Schedule Risk Analysis with Multi-Skilled Resource Scheduling to Improve Resource-Constrained Project Scheduling Problems

2021 ◽  
Vol 11 (2) ◽  
pp. 650
Author(s):  
Muritala Adebayo Isah ◽  
Byung-Soo Kim
Keyword(s):  
Risk Analysis ◽  
Project Scheduling ◽  
Resource Scheduling ◽  
Scheduling Problems ◽  
Project Schedule ◽  
Risk And Uncertainty ◽  
Resource Constrained ◽  
Resource Constrained Project Scheduling ◽  
Schedule Risk ◽  
Schedule Risk Analysis

Construction projects are planned in a complex and dynamic environment characterized by high risks and uncertainties amidst resource constraints. Assessing construction schedule risk facilitates informed decision-making, especially in a resource-constrained situation, and allows proactive actions to be taken so that project objectives are not jeopardized. This study presents a stochastic multiskilled resource scheduling (SMSRS) model for resource-constrained project scheduling problems (RCSPSP) considering the impact of risk and uncertainty on activity durations. The SMSRS model was developed by integrating a schedule risk analysis (SRA) model (developed in MS Excel) with an existing multiskilled resource scheduling (MSRS) algorithm for the development of a feasible and realistic schedule. The computational experiment carried out on three case projects using the proposed SMSRS model revealed an average percentage deviation of 10.50%, indicating the inherent risk and uncertainty in activity durations of the project schedule. The core contribution of the proposed SMSRS model is that it: (1) presents project practitioners with a simple tool for assessing the risks and uncertainty associated with resource-constrained project schedules so that necessary response actions can be taken to ensure project success; (2) provides the small-scale construction businesses with an affordable tool for evaluating schedule risk and developing a feasible and realistic project schedule.

Applying Genetic Algorithm to Resource Constrained Multi-Project Scheduling Problems

2009 ◽  
Vol 419-420 ◽  
pp. 633-636 ◽  
Author(s):  
James C. Chen ◽  
Wun Hao Jaong ◽  
Cheng Ju Sun ◽  
Hung Yu Lee ◽  
Jenn Sheng Wu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Project Scheduling ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Total Tardiness ◽  
Scheduling Problems ◽  
Test Bed ◽  
Resource Constrained ◽  
Multiple Resources ◽  
Practical Constraints

Resource-constrained multi-project scheduling problems (RCMPSP) consider precedence relationship among activities and the capacity constraints of multiple resources for multiple projects. RCMPSP are NP-hard due to these practical constraints indicating an exponential calculation time to reach optimal solution. In order to improve the speed and the performance of problem solving, heuristic approaches are widely applied to solve RCMPSP. This research proposes Hybrid Genetic Algorithm (HGA) and heuristic approach to solve RCMPSP with an objective to minimize the total tardiness. HGA is compared with three typical heuristics for RCMPSP: Maximum Total Work Content, Earliest Due Date, and Minimum Slack. Two typical RCMPSP from literature are used as a test bed for performance evaluation. The results demonstrate that HGA outperforms the three heuristic methods in term of the total tardiness.

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