Mathematical optimization offers today’s businesses a fundamentally different approach to worst-case scenario prepping. Rather than relying on gut instinct and static data, optimization leverages ...
By leveraging inference-time scaling and a novel "reflection" mechanism, ALE-Agent solves the context-drift problems that ...
Abstract: The manufacturing industry encounters numerous optimization problems, one of which is the optimization of storage location assignment (OSLA) problem in logistics. OSLA is a combinatorial ...
ABSTRACT: For solving assignment problems of staff, equipment and task in engineering support action, a 3-Dimensional assignment model is established, which contains staff skill level, equipment ...
In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...
In this study, we propose an exact method for optimizing a linear function over the efficient set of a multi-objective transportation problem (MOTP). This type of problem arises when a decision maker ...
1 Guangzhou Institute of Building Science Group Co., Ltd., Guangzhou, Guangdong, China 2 Glenn Department of Civil Engineering, Clemson University, Clemson, SC, United States Modern seismic codes ...
In the context of using DNSGA2 to solve dynamic multi-objective optimization problems (DMOPs), a critical issue arises regarding the timing of the callback function execution and its impact on ...
Heidi S. Enger ’27, an Associate Editorial Editor, is a Social Studies Concentrator in Eliot House. She’s enrolled in Ec10b this semester (don’t ask). Harvard students have to stop treating life like ...
Abstract: Most existing dynamic multiobjective evolutionary algorithms assume that the real objective function evaluations are easily acquired during the optimization process. However, in some ...
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