scholarly journals Metaheuristic Algorithms for Proactive and Reactive Project Scheduling to Minimize Contractor’s Cash Flow Gap under Random Activity Duration

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 30547-30558 ◽  
Author(s):  
Minjing Ning ◽  
Zhengwen He ◽  
Nengmin Wang ◽  
Renjing Liu
Keyword(s):  
Cash Flow ◽  
Project Scheduling ◽  
Metaheuristic Algorithms ◽  
Activity Duration ◽  
Random Activity

scholarly journals Financial optimisation of the scheduling for the multi-stage project

2017 ◽  
Vol 65 (6) ◽  
pp. 899-908
Author(s):  
M. Klimek ◽  
P. Łebkowski
Keyword(s):  
Simulated Annealing ◽  
Cash Flow ◽  
Project Scheduling ◽  
Simulated Annealing Algorithm ◽  
Cash Flows ◽  
Standard Test ◽  
Resource Constrained ◽  
Discounted Cash Flow ◽  
Multi Stage ◽  
Annealing Algorithm

AbstractThe paper analyses the problem of discounted cash flow maximising for the resource-constrained project scheduling from the project contractor’s perspective. Financial optimisation for the multi-stage project is considered. Cash outflows are the contactor’s expenses related to activity execution. Cash inflows are the client’s payments for the completed milestones. To solve the problem, the procedure of backward scheduling taking into account contractual milestones is proposed. The effectiveness of this procedure, as used to generate solutions for the simulated annealing algorithm, is verified with use of standard test instances with additionally defined cash flows and contractual milestones.

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.

scholarly journals Cost Optimal Project Scheduling

Organizacija ◽  
2008 ◽  
Vol 41 (4) ◽  
pp. 153-158
Author(s):  
Uroš Klanšek ◽  
Mirko Pšunder
Keyword(s):  
Nonlinear Programming ◽  
Objective Function ◽  
Project Scheduling ◽  
Programming Approach ◽  
Project Duration ◽  
Numerical Example ◽  
Activity Duration ◽  
The Cost ◽  
Total Project Cost ◽  
Total Project

Cost Optimal Project SchedulingThis paper presents the cost optimal project scheduling. The optimization was performed by the nonlinear programming approach, NLP. The nonlinear total project cost objective function is subjected to the rigorous system of the activity precedence relationship constraints, the activity duration constraints and the project duration constraints. The set of activity precedence relationship constraints was defined to comprise Finish-to-Start, Start-to-Start, Start-to-Finish and Finish-to-Finish precedence relationships between activities. The activity duration constraints determine relationships between minimum, maximum and possible duration of the project activities. The project duration constraints define the maximum feasible project duration. A numerical example is presented at the end of the paper in order to present the applicability of the proposed approach.

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