In response to the shortcomings of traditional computer color matching methods in color matching, visual coordination, and personalized needs, this paper introduces an intelligent color matching optimization model bas...
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This paper focuses on the utilization of multi-objective optimization algorithms, specifically the Genetic Algorithm (GA) and Multi-objective Particle Swarm optimization (MOPSO), to effectively navigate complex soluti...
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We propose a method for learning decision makers’ behavior in routing problems using inverse optimization (IO). The IO framework falls into the supervised learning category and builds on the premise that the target b...
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This study investigates bilevel optimization problems with multiple objectives at both upper and lower levels. For such problems, for every feasible solution at the upper level, there is a corresponding set of Pareto-...
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Population-based metaheuristic algorithms have been used to solve challenging optimization problems, and numerous modifications to make these algorithms more efficient have been proposed. Jaya is one of these algorith...
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Due to the presence of numerous infeasible regions in Constrained multi-objective optimization problems (CMOPs), existing algorithms struggle to identify the complete Pareto front (PF). A novel two-populations algorit...
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To address the issues of low absorption rate and high operating cost in the distributed photovoltaic power generation system within the park, a multi-objective optimization model built upon the foundation of the Inter...
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In recent years, due to the rapid development of the Chinese economy, consumers have put forward higher requirements for the delivery time of goods in online shopping, which has intensified competition among various l...
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In resource-constrained Wireless Sensor Networks, energy efficiency and lifespan are critical elements that influence the durability and efficacy of the deployed sensor network. A significant problem in wireless senso...
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To handle constrained multi-objective optimization problems (CMOPs), many constrained multi-objective evolutionary algorithms (CMOEAs) have been proposed. However, a recent study has shown that many of these CMOEAs do...
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