A Research Report on a New Framework for Solving Migrant Resettlement Using Multiobjective Evolutionary Optimization Against the backdrop of accelerated globalization and evolving socio-economic conditions, migration has become an undeniable global trend. From the perspective of humanitarian relief or the sustainable development of a globalized eco...

Breakthrough Research in Multiobjective Dynamic Flexible Job Shop Scheduling: An Innovative Approach to Optimize Biased Objectives via Multitask Learning in Genetic Programming Background Introduction Dynamic Flexible Job Shop Scheduling (DFJSS) is an essential combinatorial optimization problem with extensive real-world applications in areas such ...

The paper, titled “Higher-Order Directed Community Detection by a Multiobjective Evolutionary Framework”, authored by Jing Xiao, Jing Cao, and Xiao-Ke Xu, was published in the IEEE Transactions on Artificial Intelligence in December 2024. The authors introduce a novel approach for detecting higher-order communities in directed networks, addressing ...

Background In recent years, Reinforcement Learning (RL) has demonstrated its effectiveness in solving various complex tasks. However, many real-world decision-making and control problems involve multiple conflicting objectives. The relative importance (preference) of these objectives often needs to be balanced against each other in different scenar...