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Jian Liu, Yanyan Li, Yuankun Wang and Pengcheng Xu
The nonstationary characteristics caused by significant variation in hydrometeorological series in the context of climate change inevitably have a certain impact on the selection of an optimal gauging network. This study proposes an entropy-based, multi-...
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Chunling Ye, Zhengyan Mao and Mandan Liu
Inspired by the mechanism of generation and restriction among five elements in Chinese traditional culture, we present a novel Multi-Objective Five-Elements Cycle Optimization algorithm (MOFECO). During the optimization process of MOFECO, we use individu...
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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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Wei Li
The standard covariance matrix adaptation evolution strategy (CMA-ES) is highly effective at locating a single global optimum. However, it shows unsatisfactory performance for solving multimodal optimization problems (MMOPs). In this paper, an improved a...
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Bartosz Sawik, Javier Faulin, Elena Pérez-Bernabeu
Pág. 305 - 313
This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optima...
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Adekunle Rotimi Adekoya and Mardé Helbig
Dynamic multi-objective optimization problems (DMOPs) are optimization problems where elements of the problems, such as the objective functions and/or constraints, change with time. These problems are characterized by two or more objective functions, whe...
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Fernando Pérez-Rodríguez, Luís Nunes and João C. Azevedo
Forest management based on sustainability and multifunctionality requires reliable and user-friendly tools to address several objectives simultaneously. In this work we present FlorNExT Pro®, a multiple-criteria landscape-scale forest plan...
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Atthaphon Ariyarit and Masahiro Kanazaki
In this study, efficient global optimization (EGO) with a multi-fidelity hybrid surrogate model for multi-objective optimization is proposed to solve multi-objective real-world design problems. In the proposed approach, a design exploration is carried ou...
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Siling Feng, Ziqiang Yang and Mengxing Huang
In order to improve the performance of optimization, we apply a hybridization of adaptive biogeography-based optimization (BBO) algorithm and differential evolution (DE) to multi-objective optimization problems (MOPs). A model of multi-objective evolutio...
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Sirote Khunkitti, Apirat Siritaratiwat and Suttichai Premrudeepreechacharn
Since the increases in electricity demand, environmental awareness, and power reliability requirements, solutions of single-objective optimal power flow (OPF) and multi-objective OPF (MOOPF) (two or three objectives) problems are inadequate for modern po...
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Gyula Dörgo, János Abonyi
Pág. 210 - 225
We propose an efficient algorithm to generate Pareto optimal set of reliable molecular structures represented by group contribution methods. To effectively handle structural constraints we introduce goal oriented genetic operators to the multi-objective ...
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Yechuang Wang, Zhihua Cui and Wuchao Li
In the real word, optimization problems in multi-objective optimization (MOP) and dynamic optimization can be seen everywhere. During the last decade, among various swarm intelligence algorithms for multi-objective optimization problems, glowworm swarm o...
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Petr Kadlec
This paper aims to solve the space robot pathfinding problem, formulated as a multi-objective (MO) optimization problem with a variable number of dimensions (VND). This formulation enables the search and comparison of potential solutions with different m...
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Mariano Vargas-Santiago, Raúl Monroy, José Emmanuel Ramirez-Marquez, Chi Zhang, Diana A. Leon-Velasco and Huaxing Zhu
Leveraging human insight and intuition has been identified as having the potential for the improvement of traditional algorithmic methods. For example, in a video game, a user may not only be entertained but may also be challenged to beat the score of an...
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Francisca Santana Robles, Eva Selene Hernández-Gress, Neil Hernández-Gress and Rafael Granillo Macias
Everyday there are more disasters that require Humanitarian Supply Chain (HSC) attention; generally these problems are difficult to solve in reasonable computational time and metaheuristics (MHs) are the indicated solution algorithms. To our knowledge, t...
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Adel Younis and Zuomin Dong
The employment of conventional optimization procedures that must be repeatedly invoked during the optimization process in real-world engineering applications is hindered despite significant gains in computing power by computationally expensive models. As...
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Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke, Marcel van Herk and Tanja Alderliesten
Current state-of-the-art medical deformable image registration (DIR) methods optimize a weighted sum of key objectives of interest. Having a pre-determined weight combination that leads to high-quality results for any instance of a specific DIR problem (...
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Xiaoya Ma and Xiang Zhao
As the main feature of land use planning, land use allocation (LUA) optimization is an important means of creating a balance between the land-use supply and demand in a region and promoting the sustainable utilization of land resources. In essence, LUA o...
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Elias Munapo
Pág. 59 - 69
The paper presents a new reformulation approach to reduce the complexity of a branch and bound algorithm for solving the knapsack linear integer problem. The branch and bound algorithm in general relies on the usual strategy of first relaxing the integer...
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Binghang Lu, Christian Moya and Guang Lin
This paper presents NSGA-PINN, a multi-objective optimization framework for the effective training of physics-informed neural networks (PINNs). The proposed framework uses the non-dominated sorting genetic algorithm (NSGA-II) to enable traditional stocha...
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