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Multi-objective multi-mode resource constrained project scheduling problem using Pareto-based algorithms
by
Goli, Alireza
, Han, Tao
, Erfan Babaee Tirkolaee
, Sangaiah, Arun Kumar
, Hematian, Milad
in
Classification
/ Completion time
/ Computer simulation
/ Genetic algorithms
/ Linear programming
/ Manpower
/ Multiple objective analysis
/ Nonlinear programming
/ Production scheduling
/ Project management
/ Renewable resources
/ Resource scheduling
/ Simulated annealing
/ Sorting algorithms
2019
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Multi-objective multi-mode resource constrained project scheduling problem using Pareto-based algorithms
by
Goli, Alireza
, Han, Tao
, Erfan Babaee Tirkolaee
, Sangaiah, Arun Kumar
, Hematian, Milad
in
Classification
/ Completion time
/ Computer simulation
/ Genetic algorithms
/ Linear programming
/ Manpower
/ Multiple objective analysis
/ Nonlinear programming
/ Production scheduling
/ Project management
/ Renewable resources
/ Resource scheduling
/ Simulated annealing
/ Sorting algorithms
2019
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Multi-objective multi-mode resource constrained project scheduling problem using Pareto-based algorithms
by
Goli, Alireza
, Han, Tao
, Erfan Babaee Tirkolaee
, Sangaiah, Arun Kumar
, Hematian, Milad
in
Classification
/ Completion time
/ Computer simulation
/ Genetic algorithms
/ Linear programming
/ Manpower
/ Multiple objective analysis
/ Nonlinear programming
/ Production scheduling
/ Project management
/ Renewable resources
/ Resource scheduling
/ Simulated annealing
/ Sorting algorithms
2019
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Multi-objective multi-mode resource constrained project scheduling problem using Pareto-based algorithms
Journal Article
Multi-objective multi-mode resource constrained project scheduling problem using Pareto-based algorithms
2019
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Overview
This study addresses the multi-objective multi-mode resource-constrained project scheduling problem with payment planning where the activities can be done through one of the possible modes and the objectives are to maximize the net present value and minimize the completion time concurrently. Moreover, renewable resources including manpower, machinery, and equipment as well as non-renewable ones such as consumable resources and budget are considered to make the model closer to the real-world. To this end, a non-linear programming model is proposed to formulate the problem based on the suggested assumptions. To validate the model, several random instances are designed and solved by GAMS-BARON solver applying the ε-constraint method. For the high NP-hardness of the problem, we develop two metaheuristics of non-dominated sorting genetic algorithm II and multi-objective simulated annealing algorithm to solve the problem. Finally, the performances of the proposed solution techniques are evaluated using some well-known efficient criteria.
Publisher
Springer Nature B.V
Subject
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