Resource Constrained Multi-project Scheduling: A Priority Rule Based Evolutionary Local Search Approach

2016 ◽  
pp. 75-86 ◽  
Author(s):  
Ripon K. Chakrabortty ◽  
Ruhul A. Sarker ◽  
Daryl L. Essam
Keyword(s):  
Local Search ◽  
Project Scheduling ◽  
Priority Rule ◽  
Resource Constrained ◽  
Rule Based ◽  
A Priority ◽  
Search Approach

Robust global and local search approach to resource-constrained project scheduling

2009 ◽  
Vol 36 (3) ◽  
pp. 375-388 ◽  
Author(s):  
Jin-Lee Kim ◽  
Ralph D. Ellis
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Project Scheduling ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Resource Constrained ◽  
Resource Constrained Project Scheduling ◽  
Construction Scheduling ◽  
Computationally Intensive ◽  
Search Approach

The resource-constrained project scheduling problem (RCPSP) is one of the most challenging problems in construction scheduling applications, in which optimal solutions are of great value to project planners. This paper presents a new adaptive hybrid genetic algorithm search simulator (AHGASS) for finding an optimal solution to the problem, and provides the strategies and practical procedures to develop the algorithm. Elitist genetic algorithm (EGA) developed is used for the global search, while random walk algorithm for the local search is incorporated into the EGA to overcome the drawbacks of general genetic algorithms, which are computationally intensive and premature convergence to a local solution. Computational experiments are presented to demonstrate the performance and accuracy of AHGASS. The proposed algorithm provides a comparable and competitive performance compared with the existing genetic algorithm (GA) hybrid heuristic methods. The findings demonstrate that AHGASS has significant promise for solving a large-sized RCPSP.

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