scholarly journals A Hybrid Genetic Algorithm to Maximize Net Present Value of Project Cash Flows in Resource Constrained Project Scheduling Problem with fuzzy parameters

2016 ◽  
Vol 23 (4) ◽  
pp. 1893-1903 ◽  
Author(s):  
Fatemeh Fathallahi ◽  
Amir Abbas Najafi
Keyword(s):  
Genetic Algorithm ◽  
Project Scheduling ◽  
Net Present Value ◽  
Hybrid Genetic Algorithm ◽  
Cash Flows ◽  
Scheduling Problem ◽  
Present Value ◽  
Resource Constrained ◽  
Project Scheduling Problem ◽  
Fuzzy Parameters

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.

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