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Son PVH, Khoi LNQ. Application of slime mold algorithm to optimize time, cost and quality in construction projects. INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT 2023. [DOI: 10.1080/15623599.2023.2174660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Affiliation(s)
- Pham Vu Hong Son
- Construction Engineering & Management Department, Ho Chi Minh City University of Technology (HCMUT), Vietnam National University, Ho Chi Minh City, Vietnam
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Son PVH, Khoi LNQ. Utilizing artificial intelligence to solving time - cost - quality trade-off problem. Sci Rep 2022; 12:20112. [PMID: 36418454 PMCID: PMC9684541 DOI: 10.1038/s41598-022-24668-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 11/18/2022] [Indexed: 11/25/2022] Open
Abstract
This study presents the Slime Mold Algorithm (SMA) to solve the time-cost-quality trade-off problem in a construction project. The proposed SMA is a flexible and efficient algorithm in exploration and exploitation to reach the best optimal solution to process the input model's data. This paper aims to discuss and solve the optimization problem and compare the evaluation with other algorithms such as Opposition-based Multiple Objective Differential Evolution, Non-dominated sorting genetic algorithm, Multiple objective particle swarm optimization, Multiple objective differential evolution and Chaotic initialized multiple objective differential evolution (CAMODE) to verify the efficiency and potential of the proposed algorithm. According to the analysis results, the SMA model generated a diversification measure for case studies, producing superior outcomes to those of previous algorithms.
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Affiliation(s)
- Pham Vu Hong Son
- grid.444828.60000 0001 0111 2723Construction Engineering & Management Department, Ho Chi Minh City University of Technology (HCMUT), Vietnam National University, 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, 700000 Vietnam
| | - Luu Ngoc Quynh Khoi
- grid.444828.60000 0001 0111 2723Construction Engineering & Management Department, Ho Chi Minh City University of Technology (HCMUT), Vietnam National University, 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, 700000 Vietnam
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Ghasemi M, Akbari E, Faraji Davoudkhani I, Rahimnejad A, Asadpoor MB, Gadsden SA. Application of Coulomb’s and Franklin’s laws algorithm to solve large-scale optimal reactive power dispatch problems. Soft comput 2022. [DOI: 10.1007/s00500-022-07417-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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The Optimal and Economic Planning of a Power System Based on the Microgrid Concept with a Modified Seagull Optimization Algorithm Integrating Renewable Resources. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12094743] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
In the past, planning to develop an electricity generation capacity supply of consumable load, an acceptable level of reliability, and minimum cost has played significant roles. Due to technological development in energy and the support of energy policymakers to make the most of these clean and cheap resources, a significant amount of research has been conducted to make the most of such energy. Constraints such as low capacity, output power uncertainty, and sustainability problems have made using distributed energy sources costly and complex. Theoretically, capacity development planning in a power system is part of macro-energy planning. It is generally based on specific development policies in each country’s national interest. In addition to being economical, the purpose of this planning was to find the best capacity development plan commensurate with the amount of consumption so that the development plan does not go beyond the permissible limits of reliability, environmental issues, and other constraints. On the other hand, due to the considerable growth of divided production, especially energy sources, it is essential to use microgrids. Accordingly, in this research study, in the process of solving the problem of planning and providing load growth by the distributed generation units to maximize reliability and minimize investment costs, the creation of smaller networks was investigated. To optimize zoning, the weighted graph theory method, in which the weight of the edges is the apparent power passing through the lines, was adopted. In addition, reactive power reliability was included in the calculations to improve the economic aspects. Probabilistic modeling for the presence of renewable resources was employed to bring the model to reality. Since the above problem is very complex, a Seagull-based algorithm and chaos theory were utilized to solve this matter. Finally, the suggested method for the sample system is discussed in different scenarios, indicating an improvement in the system’s performance. According to the numerical results, the NSGA, SPEA, and MOPSO have mean values of 68.3%, 50.2%, and 48.3%, which are covered by the proposed optimization algorithm.
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Wang W, Dai S, Zhao W, Wang C. Multi-objective optimization of hexahedral pyramid crash box using MOEA/D-DAE algorithm. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.108481] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Solution of multi-objective transportation-p-facility location problem with effect of variable carbon emission by evolutionary algorithms. Soft comput 2021. [DOI: 10.1007/s00500-021-05619-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Zand M, Chamorro HR, Nasab MA, Hosseinian SH. Optimal reactive power dispatch using θ-social mimic optimization (θ-SMO). JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020. [DOI: 10.3233/jifs-201667] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The social mimic optimization algorithm (SMO) and its enhanced version (θ-SMO) is presented in the current study for the optimal dispatch problem of the reactive power (ORPD) with continuous and discrete control variables in the IEEE standard networks. The feasibleness and functioning of the θ-SMO and SMO algorithms are indicated for the IEEE 57-bus, and IEEE 118-bus standard networks. The outcomes of the simulation were compared, and it was shown that the optimization efficacy of these algorithms is higher than other rooted algorithms, such as optics in-spired optimization (OIO), the social spider algorithm (SSA) algorithm, and biogeography-based optimization (BBO). Results obtained for ORPD problem indicate better performance concerning the θ-SMO algorithm’s solution quality compared to original SMO algorithm and other algorithms.
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Affiliation(s)
- Mohammad Zand
- Young Researchers and Elite Club, Hamedan Branch, Islamic Azad University, Hamedan, Iran
| | | | - Morteza Azimi Nasab
- Young Researchers and Elite Club, Borujerd Branch, Islamic Azad University, Borujerd, Iran
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Research on Collaborative Planning and Symmetric Scheduling for Parallel Shipbuilding Projects in the Open Distributed Manufacturing Environment. Symmetry (Basel) 2020. [DOI: 10.3390/sym12010161] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
In the current distributed manufacturing environment, more extensive enterprise cooperation is an effective means for shipbuilding companies to increase the competitiveness. However, considering the project scale and the uneven production capacity between the collaborative enterprises, a key issue for shipbuilding companies is to effectively combine the product-oriented project tasks and the specialized production-oriented plants. Due to information privatization, the decision-making process of project planning and scheduling is distributed and symmetric. Existing project scheduling methods and collaboration mechanisms in the shipbuilding industry are somehow inefficient. The aim of the research is to provide an assistant decision-making method to support effective task dispatching and multi-party cooperation for better utilization of the distributed resources and to help project managers control the shipbuilding process. The article initially establishes an agent-based complex shipbuilding project collaborative planning and symmetric scheduling framework, simulating the distributed collaborative decision-making process and bridging the multi-project planning with the individual project scheduling in much detail, which fills the research gap. A negotiation method based on iterative combination auction (ICA) is further proposed to solve the integration problem of project planning and task scheduling, and an illustrative example is conducted to demonstrate the effectiveness and rationality of the methods. Finally, an application case using a prototype system on shipbuilding projects collaborative planning and scheduling will be reported as a result.
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Sun R, Liu Y, Zhu H, Azizipanah-Abarghooee R, Terzija V. A network reconfiguration approach for power system restoration based on preference-based multiobjective optimization. Appl Soft Comput 2019. [DOI: 10.1016/j.asoc.2019.105656] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Ibrahim AO, Shamsuddin SM, Abraham A, Qasem SN. Adaptive memetic method of multi-objective genetic evolutionary algorithm for backpropagation neural network. Neural Comput Appl 2019. [DOI: 10.1007/s00521-018-03990-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Gap-Filling of MODIS Fractional Snow Cover Products via Non-Local Spatio-Temporal Filtering Based on Machine Learning Techniques. REMOTE SENSING 2019. [DOI: 10.3390/rs11010090] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Cloud obscuration leaves significant gaps in MODIS snow cover products. In this study, an innovative gap-filling method based on the concept of non-local spatio-temporal filtering (NSTF) is proposed to reconstruct the cloud gaps in MODIS fractional snow cover (SCF) products. The ground information of a gap pixel was estimated by using the appropriate similar pixels in the remaining known part of an image via an automatic machine learning technique. We take the MODIS SCF product cloud gap filling data from 2001 to 2016 in Northern Xinjiang, China as an example. The results demonstrate that the methodology can generate almost continuous spatio-temporal, daily MODIS SCF images, and it leaves only 0.52% of cloud gaps long-term, on average. The validation results based on “cloud assumption” exhibit high accuracy, with a higher R 2 exceeding 0.8, a lower RMSE of 0.1, an overestimated error of 1.13%, an underestimated error of 1.4%, and a spatial efficiency (SPAEF) of 0.78. The validation based on 50 in situ snow depth observations demonstrates the superiority of the methodology in terms of accuracy and consistency. The overall accuracy is 93.72%. The average omission and commission error have increased approximately 1.16 and 0.53% compared with the original MODIS SCF products under a clear sky term.
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Luong DL, Tran DH, Nguyen PT. Optimizing multi-mode time-cost-quality trade-off of construction project using opposition multiple objective difference evolution. INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT 2018. [DOI: 10.1080/15623599.2018.1526630] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Duc-Long Luong
- Department of Construction Engineering and Management, Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam
| | - Duc-Hoc Tran
- Department of Construction Engineering and Management, Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam
| | - Phong Thanh Nguyen
- Department of Project Management, Faculty of Civil Engineering, Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam
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Heidari AA, Ali Abbaspour R, Rezaee Jordehi A. Gaussian bare-bones water cycle algorithm for optimal reactive power dispatch in electrical power systems. Appl Soft Comput 2017. [DOI: 10.1016/j.asoc.2017.04.048] [Citation(s) in RCA: 75] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Shaheen AM, El-Sehiemy RA, Farrag SM. A reactive power planning procedure considering iterative identification of VAR candidate buses. Neural Comput Appl 2017. [DOI: 10.1007/s00521-017-3098-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Hasanvand S, Nayeripour M, Waffenschmidt E, Fallahzadeh-Abarghouei H. A new approach to transform an existing distribution network into a set of micro-grids for enhancing reliability and sustainability. Appl Soft Comput 2017. [DOI: 10.1016/j.asoc.2016.12.013] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Rosenthal S, Borschbach M. Design Perspectives of an Evolutionary Process for Multi-objective Molecular Optimization. LECTURE NOTES IN COMPUTER SCIENCE 2017. [DOI: 10.1007/978-3-319-54157-0_36] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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Hassanzadeh A, Rasti-Barzoki M, Khosroshahi H. Two new meta-heuristics for a bi-objective supply chain scheduling problem in flow-shop environment. Appl Soft Comput 2016. [DOI: 10.1016/j.asoc.2016.08.019] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Sun G, Zhang A, Jia X, Li X, Ji S, Wang Z. DMMOGSA: Diversity-enhanced and memory-based multi-objective gravitational search algorithm. Inf Sci (N Y) 2016. [DOI: 10.1016/j.ins.2016.05.007] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Yliniemi L, Tumer K. Multi-objective multiagent credit assignment in reinforcement learning and NSGA-II. Soft comput 2016. [DOI: 10.1007/s00500-016-2124-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Sidi MMO, Quilot-Turion B, Kadrani A, Génard M, Lescourret F. The Relationship between Metaheuristics Stopping Criteria and Performances. INTERNATIONAL JOURNAL OF APPLIED METAHEURISTIC COMPUTING 2014. [DOI: 10.4018/ijamc.2014070104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
A major difficulty in the use of metaheuristics (i.e. evolutionary and particle swarm algorithms) to deal with multi-objective optimization problems is the choice of a convenient point at which to stop computation. Indeed, it is difficult to find the best compromise between the stopping criterion and the algorithm performance. This paper addresses this issue using the Non-dominated Sorting Genetic Algorithm (NSGA-II) and the Multi-Objective Particle Swarm Optimization with Crowding Distance (MOPSO-CD) for the model-based design of sustainable peach fruits. The optimization problem of interest contains three objectives: maximize fruit fresh mass, maximize fruit sugar content, and minimize the crack density on the fruit skin. This last objective targets a reduction in the use of fungicides and can thus enhance preservation of the environment and human health. Two versions of the NSGA-II and two of the MOPSO-CD were applied to tackle this difficult optimization problem: the original versions with a maximum number of generations used as stopping criterion and modified versions using the stopping criterion proposed by the authors of (Roudenko & Schoenauer, 2004). This second stopping criterion is based on the stabilization of the maximal crowding distance and aims to stop computation when many generations are performed without further improvement in the quality of the solutions. A benchmark consisting of four plant management scenarios has been used to compare the performances of the original versions (OV) and the modified versions (MV) of the NSGA-II and the MOPSO-CD. Twelve independent simulations were performed for each version and for each scenario, and a high number of generations were generated for the OV (e.g., 1500 for the NSGA-II and 200 for the MOPSO-CD). This paper compares the performances of the two versions of both algorithms using four standard metrics and statistical tests. For both algorithms, the MV obtained solutions similar in quality to those of the OV but after significantly fewer generations. The resulting reduction in computational time for the optimization step will provide opportunities for further studies on the sustainability of peach ideotypes.
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Affiliation(s)
- Mohamed-Mahmoud Ould Sidi
- UR 1115 Plantes et Systèmes de Culture Horticoles, Institut National de la Recherche Agronomique (INRA), Avignon, France
| | - Bénédicte Quilot-Turion
- UR 1052 Génétique et Amélioration des Fruits et Légumes, Institut National de la Recherche Agronomique (INRA), Montfavet, France
| | - Abdeslam Kadrani
- Mathematics and Operation Research, Institut National de Statistique et Economie Appliquée (INSEA), Rabat, Morocco
| | - Michel Génard
- UR 1115 Plantes et Systèmes de Culture Horticoles, Institut National de la Recherche Agronomique (INRA), Avignon, France
| | - Françoise Lescourret
- UR 1115 Plantes et Systèmes de Culture Horticoles, Institut National de la Recherche Agronomique (INRA), Avignon, France
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