9 papers
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…
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…
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…
Fairness-Aware Performance Evaluation for Multi-Party Multi-Objective Optimization
Zifan Zhao, Peilan Xu, Wenjian Luo
In multiparty multiobjective optimization problems, solution sets are usually evaluated using classical performance metrics, aggregated across DMs. However, such mean-based evaluat…
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…
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…
Runtime Analysis of Evolutionary Algorithms for Multi-party Multi-objective Optimization
Yuetong Sun, Peilan Xu, Wenjian Luo
In scenarios where multiple decision-makers operate within a common decision space, each focusing on their own multi-objective optimization problem (e.g., bargaining games), the pr…
Evolutionary Trigger Detection and Lightweight Model Repair Based Backdoor Defense
Qi Zhou, Zipeng Ye, Yubo Tang +3
Deep Neural Networks (DNNs) have been widely used in many areas such as autonomous driving and face recognition. However, DNN model is fragile to backdoor attack. A backdoor in the…
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…