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Te Ye

2 accepted papers

2023

Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization

NeurIPS 2023poster

Recently, neural heuristics based on deep reinforcement learning have exhibited promise in solving multi-objective combinatorial optimization problems (MOCOPs). However, they are still struggling to achieve high learning efficiency and solution quality. To tackle this issue, we propose an efficient…

2023

Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement

NeurIPS 2023poster

Most of existing neural methods for multi-objective combinatorial optimization (MOCO) problems solely rely on decomposition, which often leads to repetitive solutions for the respective subproblems, thus a limited Pareto set. Beyond decomposition, we propose a novel neural heuristic with diversity e…