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20242026
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cs.AI2026

Robust Metaheuristics under Uncertainty for Berth Allocation and Quay Crane Assignment: A Review

Peilan Xu, Yang Li, Wenjian Luo

The berth allocation and quay crane assignment problem (BACAP) is a representative port-terminal scheduling problem in maritime transportation and freight logistics, where vessel a…

cs.AI2026

Structure-Conditioned Actor-Critic Branches for Quality-Diversity Reinforcement Learning

Lianrong Zuo, Peilan Xu, Yong Liu +1

Quality-diversity reinforcement learning (QD-RL) aims to construct policy repertoires that contain both high-performing and behaviorally diverse policies. Existing QD-RL methods ma…

cs.AI2026

Multi-Party Multi-Objective Optimization as Consensus Search: Runtime Analysis of Cross-Party Recombination

Xiaolei Fang, Peilan Xu, Wenjian Luo

Multi-party multi-objective optimization problems (MPMOPs) require consensus among autonomous decision makers and therefore differ from flattened many-objective formulations. Exist…

cs.AI2025

MIR: Efficient Exploration in Episodic Multi-Agent Reinforcement Learning via Mutual Intrinsic Reward

Kesheng Chen, Wenjian Luo, Bang Zhang +2

Episodic rewards present a significant challenge in reinforcement learning. While intrinsic reward methods have demonstrated effectiveness in single-agent rein-forcement learning s…

cs.AI2025

Decomposability-Guided Cooperative Coevolution for Large-Scale Itinerary Planning

Ziyu Zhang, Peilan Xu, Yuetong Sun +2

Large-scale itinerary planning is a variant of the traveling salesman problem, aiming to determine an optimal path that maximizes the collected point-of-interest (POI) scores while…

cs.AI2024

Benchmark for CEC 2024 Competition on Multiparty Multiobjective Optimization

Wenjian Luo, Peilan Xu, Shengxiang Yang +1

The competition focuses on Multiparty Multiobjective Optimization Problems (MPMOPs), where multiple decision makers have conflicting objectives, as seen in applications like UAV pa…