A Multi-Objective Imperialist Competitive Algorithm for solving discrete time, cost and quality trade-off problems with mode-identity and resource-constrained situations

2014 ◽  
Vol 50 ◽  
pp. 80-96 ◽  
Author(s):  
Elham Nabipoor Afruzi ◽  
Amir Abbas Najafi ◽  
Emad Roghanian ◽  
Mostafa Mazinani
Keyword(s):  
Discrete Time ◽  
Imperialist Competitive Algorithm ◽  
Time Cost ◽  
Resource Constrained ◽  
Trade Off ◽  
Multi Objective ◽  
Competitive Algorithm

scholarly journals Fuzzy-multi-mode Resource-constrained Discrete Time-cost-resource Optimization in Project Scheduling Using ENSCBO

2021 ◽  
Author(s):  
Ali Kaveh ◽  
Farivar Rajabi
Keyword(s):  
Discrete Time ◽  
Project Planning ◽  
Resource Optimization ◽  
Time Cost ◽  
Resource Constrained ◽  
Planning And Scheduling ◽  
Multi Objective ◽  
Construction Companies ◽  
Resource Leveling ◽  
Multi Mode

Construction companies are required to employ effective methods of project planning and scheduling in today's competitive environment. Time and cost are critical factors in project success, and they can vary based on the type and amount of resources used for activities, such as labor, tools, and materials. In addition, resource leveling strategies that are used to limit fluctuations in a project's resource consumption also affect project time and cost. The multi-mode resource-constrained discrete-time–cost-resource optimization (MRC-DTCRO) is an optimization tool that is developed for scheduling of a set of activities involving multiple execution modes with the aim of minimizing time, cost, and resource moment. Moreover, uncertainty in cost should be accounted for in project planning because activities are exposed to risks that can cause delays and budget overruns. This paper presents a fuzzy-multi-mode resource-constrained discrete-time–cost-resource optimization (F-MRC-DTCRO) model for the time-cost-resource moment tradeoff in a fuzzy environment while satisfying all the project constraints. In the proposed model, fuzzy numbers are used to characterize the uncertainty of direct cost of activities. Using this model, different risk acceptance levels of the decision maker can be addressed in the optimization process. A newly developed multi-objective optimization algorithm called ENSCBO is used to search non-dominated solutions to the fuzzy multi-objective model. Finally, the developed model is applied to solve a benchmark test problem. The results indicate that incorporating the fuzzy structure of uncertainty in costs to previously developed MRC-DTCRO models facilitates the decision-making process and provides more realistic solutions.

MOICA: A novel multi-objective approach based on imperialist competitive algorithm

2013 ◽  
Vol 219 (17) ◽  
pp. 8829-8841 ◽  
Author(s):  
Rasul Enayatifar ◽  
Moslem Yousefi ◽  
Abdul Hanan Abdullah ◽  
Amer Nordin Darus
Keyword(s):  
Imperialist Competitive Algorithm ◽  
Multi Objective ◽  
Competitive Algorithm

scholarly journals New Computational Results on the Discrete Time/Cost Trade-Off Problem in Project Networks

1998 ◽  
Vol 49 (11) ◽  
pp. 1153 ◽  
Author(s):  
E. Demeulemeester ◽  
B. De Reyck ◽  
B. Foubert ◽  
W. Herroelen ◽  
M. Vanhoucke
Keyword(s):  
Discrete Time ◽  
Computational Results ◽  
Time Cost ◽  
Trade Off ◽  
Project Networks

The discrete time/cost trade-off problem: extensions and heuristic procedures

2007 ◽  
Vol 10 (4-5) ◽  
pp. 311-326 ◽  
Author(s):  
Mario Vanhoucke ◽  
Dieter Debels
Keyword(s):  
Discrete Time ◽  
Time Cost ◽  
Trade Off ◽  
Heuristic Procedures
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