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Jiaxu Ning, Changsheng Zhang, Peng Sun and Yunfei Feng
In recent years, when solving MOPs, especially discrete path optimization problems, MOACOs concerning other meta-heuristic algorithms have been used and improved often, and they have become a hot research topic. This article will start from the basic pro...
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Jiajia Fan, Wentao Huang, Qingchao Jiang and Qinqin Fan
For multimodal multi-objective optimization problems (MMOPs), there are multiple equivalent Pareto optimal solutions in the decision space that are corresponding to the same objective value. Therefore, the main tasks of multimodal multi-objective optimiz...
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Juarez Machado da Silva, Gabriel de Oliveira Ramos and Jorge Luis Victória Barbosa
The Shortest Path (SP) problem resembles a variety of real-world situations where one needs to find paths between origins and destinations. A generalization of the SP is the Dynamic Shortest Path (DSP) problem, which also models changes in the graph at a...
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Zitong Wang, Yan Pei and Jianqiang Li
The multi-objective optimization problem is difficult to solve with conventional optimization methods and algorithms because there are conflicts among several optimization objectives and functions. Through the efforts of researchers and experts from diff...
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Shaswot Shresthamali, Masaaki Kondo and Hiroshi Nakamura
IoT embedded systems have multiple objectives that need to be maximized simultaneously. These objectives conflict with each other due to limited resources and tradeoffs that need to be made. This requires multi-objective optimization (MOO) and multiple P...
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Amr Mohamed AbdelAziz, Taysir Hassan A. Soliman, Kareem Kamal A. Ghany and Adel Abu El-Magd Sewisy
Multi-Objective Problems (MOPs) are common real-life problems that can be found in different fields, such as bioinformatics and scheduling. Pareto Optimization (PO) is a popular method for solving MOPs, which optimizes all objectives simultaneously. It p...
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Gilberto Reynoso-Meza, Victor Henrique Alves Ribeiro and Elizabeth Pauline Carreño-Alvarado
Dealing with real world engineering problems, often comes with facing multiple and conflicting objectives and requirements. Water distributions systems (WDS) are not exempt from this: while cost and hydraulic performance are usually conflicting objective...
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Kyle Erwin and Andries Engelbrecht
Portfolio optimization is a multi-objective optimization problem (MOOP) with risk and profit, or some form of the two, as competing objectives. Single-objective portfolio optimization requires a trade-off coefficient to be specified in order to balance t...
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Praveen Kumar Shukla and Surya Prakash Tripathi
Interpretability and accuracy are two important features of fuzzy systems which are conflicting in their nature. One can be improved at the cost of the other and this situation is identified as ?Interpretability-Accuracy Trade-Off?. To deal with this tra...
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Xiaolan Li, Bingbo Gao, Zhongke Bai, Yuchun Pan and Yunbing Gao
Complex geographical spatial sampling usually encounters various multi-objective optimization problems, for which effective multi-objective optimization algorithms are much needed to help advance the field. To improve the computational efficiency of the ...
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Qasem Al-Tashi, Emelia Akashah Patah Akhir, Said Jadid Abdulkadir, Seyedali Mirjalili, Tareq M. Shami, Hitham Alhusssian, Alawi Alqushaibi, Ayed Alwadain, Abdullateef O. Balogun and Nasser Al-Zidi
The accurate classification of reservoir recovery factor is dampened by irregularities such as noisy and high-dimensional features associated with the reservoir measurements or characterization. These irregularities, especially a larger number of feature...
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Tianlong Jia, Hui Qin, Dong Yan, Zhendong Zhang, Bin Liu, Chaoshun Li, Jinwen Wang and Jianzhong Zhou
Traditional reservoir operation mainly focuses on economic benefits, while ignoring the impacts on navigation. Thus, the economic operation of reservoirs considering navigational demands is of great significance for improving benefits. A navigation capac...
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Young Hwan Choi and Joong Hoon Kim
This study compares the performance of self-adaptive optimization approaches in efficient water distribution systems (WDS) design and presents a guide for the selection of the appropriate method employing optimization utilizing the characteristic of each...
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Tomé Sicuaio, Pengxiang Zhao, Petter Pilesjo, Andrey Shindyapin and Ali Mansourian
Land use allocation (LUA) is of prime importance for the development of urban sustainability and resilience. Since the process of planning and managing land use requires balancing different conflicting social, economic, and environmental factors, it has ...
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Yongyu Qu, Bo Song, Shubing Cai, Pinzeng Rao and Xichen Lin
Recently, the Chinese government has implemented stringent water requirements based on the concept of ?Basing four aspects on water resources?. However, existing research has inadequately addressed the constraints of water resources on population, city b...
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Jianbo Liao, Shuang Li, Yihong Liu, Siyuan Mao, Tuo Tian, Xueyan Ma, Bing Li and Yong Qiu
It is essential to reduce carbon emissions in wastewater treatment plants (WWTPs) to achieve carbon neutrality in society. However, current optimization of WWTPs prioritizes the operation cost index (OCI) and effluent quality index (EQI) over greenhouse ...
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Yawei Ning, Minglei Ren, Shuai Guo, Guohua Liang, Bin He, Xiaoyang Liu and Rong Tang
Multi-objective reservoir operation of reservoir flood control involves numerous factors and complex model solving, and exploring effective methods for solving the operation models has always been a hot topic in reservoir optimization operation research....
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Jafar Jafari-Asl, Seyed Arman Hashemi Monfared and Soroush Abolfathi
This study investigates the optimal and safe operation of pumping stations in water distribution systems (WDSs) with the aim of reducing the environmental footprint of water conveyance processes. We introduced the nonlinear chaotic honey badger algorithm...
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Saile Zhang, Qingzhen Yang, Rui Wang and Xufei Wang
The use of traditional optimization methods in engineering design problems, specifically in aerodynamic and infrared stealth optimization for engine nozzles, requires a large number of objective function evaluations, therefore introducing a considerable ...
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Ping Huang and Yafeng Wu
Airborne speech enhancement is always a major challenge for the security of airborne systems. Recently, multi-objective learning technology has become one of the mainstream methods of monaural speech enhancement. In this paper, we propose a novel multi-o...
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