meta-heuristic algorithms
Sajad Janbaz; Seyed Mohammadreza Davoodi; Abdolmajid Abdolbaghi Ataabadi
Abstract
Purpose: The current research aims to present a multi-objective mathematical model with an integrated approach to scheduling and financial flow in production projects using Non-dominated Sorting Genetic Algorithm II (NSGA-II).Methodology: This research presents a multi-objective mathematical model integrating ...
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Purpose: The current research aims to present a multi-objective mathematical model with an integrated approach to scheduling and financial flow in production projects using Non-dominated Sorting Genetic Algorithm II (NSGA-II).Methodology: This research presents a multi-objective mathematical model integrating scheduling and financial flow optimization in civil engineering projects. This research addresses the scheduling and financial flow challenges in construction companies' production projects. The objective is to develop a multi-objective mathematical model that integrates scheduling and financial considerations to optimize resource allocation and minimize costs. The statistical population is in the form of a case study, and the required information and data were collected through interviews with managers of Kisson Construction Company.Findings: NSGA-II was used as an optimization algorithm to find efficient multi-objective solutions, and optimal results were presented to select civil and construction projects.Originality/Value: This research contributes to the field by proposing a novel multi-objective mathematical model that integrates scheduling and financial flow considerations in production projects. The use of the NSGA-II algorithm enhances the efficiency of finding optimal solutions. The findings can be valuable for decision-making when selecting construction and production projects.
Scheduling Modeling
Ali Husseinzadeh Kashan; Saeed Afkhami; Parisa Maroofkhani
Abstract
Purpose: In this research due to the importance of the U-shaped assembly line balancing and, on the other hand, the importance of human factors and setup times, we want to develop a bi-objective mathematical model minimize the cycle time and the total cost.Methodology: Since the research problem is shown ...
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Purpose: In this research due to the importance of the U-shaped assembly line balancing and, on the other hand, the importance of human factors and setup times, we want to develop a bi-objective mathematical model minimize the cycle time and the total cost.Methodology: Since the research problem is shown to be NP-hard, NSGA-II, which is a population-based algorithm, and also SPEA-II are used to solve the problem.Findings: A mathematical model for the problem on hand is developed. We solve the problem using NSGA-II and SPEA-II. We use four criteria for analyzing the results of the mathematical model and evaluating the performance of the multi-objective evolutionary algorithms. The experimental results demonstrate that NSGA-II is superior to SPEA-II.Originality/Value: A bi-objective mathematical model for the U-shaped assembly line balancing problem considering setup-times and workers' skill is developed, and the problem is solved using two algorithms.