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Rectangle expansion A* pathfinding for grid maps

Chinese Journal of Aeronautics 2016年第5期29卷 1385-1396页

作者： Zhang An Li Chong Bi Wenhao School of Aeronautics Northwestern Polytechnical University School of Electronics and Information Northwestern Polytechnical University

search speed, quality of resulting paths and the cost of pre-processing are the principle evaluation metrics of a pathfinding algorithm. In this paper, a new algorithm for grid-based maps, rectangle expansion A＊（REA＊）, is presented that improves the performance of A＊ significantly. REA＊ explores maps in units of unblocked rectangles. All unnecessary points inside the rectangles are pruned and boundaries of the rectangles （instead of individual points within those boundaries） are used as search nodes. This makes the algorithm plot fewer points and have a much shorter open list than A＊. REA＊ returns jump and grid-optimal path points, but since the line of sight between jump points is protected by the unblocked rectangles, the resulting path of REA＂ is usually better than grid-optimal. The algorithm is entirely online and requires no offline pre-processing. Experimental results for typical benchmark problem sets show that REA＊ can speed up a highly optimized A＊ by an order of magnitude and more while preserving completeness and optimality. This new algorithm is competitive with other highly successful variants of A＊.

关键词： Breaking path symmetries Grid Heuristic algorithms path search Variant of A*

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A Novel Integrated path Planning Algorithm for Warehouse AGVs

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Chinese Journal of Electronics 2021年第2期30卷 331-338页

作者： WEN Tao YANG Daichuan LIU Weifeng WEN Chenglin CAI Baigen School of Electronic and Information Engineering Beijing Jiaotong University School of Automation Hangzhou Dianzi University

We propose an integrated path planning method for multiple automated guided vehicles performing logistics delivery within a real-world warehouse environment considering obstacles. By applying it on each vehicle,this proposed method enables the vehicle the vehicles have the capabilities for autonomous path planning. The path planning consists of three parts, K-means algorithm based task points clustering, genetic algorithm based task points ordering, and the probabilistic road map based best path search. Vehicle conflict resolution is depending on implementing the probabilistic road map construction considering the realistic map with *** simulations result validate that the clustering and ordering are necessary for the path planning, both the path planning time and the Automated guided vehicles(AGVs)running time can be dramatically reduced.

关键词： path planning time vehicle conflict resolution real-world warehouse environment probabilistic road map construction path planning collision avoidance integrated path planning method mobile robots autonomous path planning genetic algorithm algorithm based task points path search vehicles running time novel integrated path planning algorithm logistics genetic algorithms automatic guided vehicles multiple automated guided vehicles logistics delivery

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Novel Positive Multi-Layer Graph Based Method for Collaborative Filtering Recommender Systems

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Journal of Computer Science & Technology 2022年第4期37卷 975-990页

作者： Bushra Alhijawi Ghazi AL-Naymat Department of Computer Science Princess Sumaya University for TechnologyAmman 11941Jordan Artificial Intelligence Research Center College of Engineering and Information TechnologyAjman UniversityAjman 20550U.A.E.

Recommender systems play an increasingly important role in a wide variety of applications to help users find favorite products. Collaborative filtering has remarkable success in terms of accuracy and becomes one of the most popular recommendation methods. However, these methods have shown unpretentious performance in terms of novelty, diversity, and coverage. We propose a novel graph-based collaborative filtering method, namely Positive Multi-Layer Graph-Based Recommender System (PMLG-RS). PMLG-RS involves a positive multi-layer graph and a path search algorithm to generate recommendations. The positive multi-layer graph consists of two connected layers: the user and item layers. PMLG-RS requires developing a new path search method that finds the shortest path with the highest cost from a source node to every other node. A set of experiments are conducted to compare the PMLG-RS with well-known recommendation methods based on three benchmark datasets, MovieLens-100K, MovieLens-Last, and Film Trust. The results demonstrate the superiority of PMLG-RS and its high capability in making relevant, novel, and diverse recommendations for users.

关键词： recommender system collaborative filtering graph theory path search novelty coverage diversity

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