A graphical processing unit‐based parallel hybrid genetic algorithm for resource‐constrained multi‐project scheduling problem

2021 ◽  
Author(s):  
Furkan Uysal ◽  
Rifat Sonmez ◽  
Selcuk Kursat Isleyen
Keyword(s):  
Genetic Algorithm ◽  
Project Scheduling ◽  
Hybrid Genetic Algorithm ◽  
Graphical Processing Unit ◽  
Processing Unit ◽  
Scheduling Problem ◽  
Resource Constrained ◽  
Parallel Hybrid ◽  
Project Scheduling Problem ◽  
Graphical Processing

Development of Hybrid Genetic Algorithms for the Resource Constrained Multi-Project Scheduling Problem

2005 ◽  
Author(s):  
Wenjian Liu ◽  
Jinghua Li
Keyword(s):  
Genetic Algorithm ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Hybrid Genetic Algorithm ◽  
Second Phase ◽  
Scheduling Problem ◽  
Priority Rules ◽  
Resource Constrained ◽  
Chromosome Representation ◽  
Project Scheduling Problem

In multi-project environment, multiple projects share and compete for the limited resources to achieve their own goals. Besides resource constraints, there exist precedence constraints among activities within each project. This paper presents a hybrid genetic algorithm to solve the resource-constrained multi-project scheduling problem (RCMPSP), which is well known NP-hard problem. Objectives described in this paper are to minimize total project time of multiple projects. The chromosome representation of the problem is based on activity lists. The proposed algorithm was operated in two phases. In the first phase, the feasible schedules are constructed as the initialization of the algorithm by permutation based simulation and priority rules. In the second phase, this feasible schedule was optimized by genetic algorithm, thus a better approximate solution was obtained. Finally, after comparing several different algorithms, the validity of proposed algorithm is shown by a practical example.

Project Scheduling Problem with Stochastic Resource-Dependent Activity Duration

2013 ◽  
Vol 483 ◽  
pp. 607-610 ◽  
Author(s):  
Chun Jie Zhong ◽  
Ying Yu ◽  
Yun Lang Jia
Keyword(s):  
Genetic Algorithm ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Project Scheduling ◽  
Point Method ◽  
Scheduling Problem ◽  
Resource Constrained ◽  
Activity Duration ◽  
Dependent Activity ◽  
Project Scheduling Problem

A resource-constrained project scheduling problem with stochastic resource-dependent activity durations is presented in this paper,and the two-point method is employed to simulate the uncertain property.Furthermore a genetic algorithm combined with this method is provided to solve the problem. Compared with the results from the genetic with Monte Carlo simulation, the proposed method is verified to be effective and more efficient.

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