Hongle Li¹, SeongKi Kim^2,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 473-492, 2024, DOI:10.32604/cmc.2024.048402

Abstract Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetables and determines the stop and the start according to the demands. This study explores the optimization of dynamic vehicle scheduling and real-time route planning in urban public transportation systems, with a focus on bus services. It addresses the limitations of current shared mobility routing algorithms, which are primarily designed for simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. The research introduces an route planning algorithm designed to dynamically accommodate passenger travel needs and enable real-time route modifications.… More >

Xinci Zhou, Jin Zhu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2705-2727, 2024, DOI:10.32604/cmes.2024.046363

Abstract As the number of automated guided vehicles (AGVs) within automated container terminals (ACT) continues to rise, conflicts have become more frequent. Addressing point and edge conflicts of AGVs, a multi-AGV conflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards. For larger terminal maps and complex environments, the grid method is employed to model AGVs’ road networks. An improved bounded conflict-based search (IBCBS) algorithm tailored to ACT is proposed, leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range. Comparative experiments involving 60… More >

Abdulwahab Ali Almazroi^1,*, Nasir Ayub²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3921-3942, 2023, DOI:10.32604/cmc.2023.046602

Abstract Effectively managing complex logistics data is essential for development sustainability and growth, especially in optimizing distribution routes. This article addresses the limitations of current logistics path optimization methods, such as inefficiencies and high operational costs. To overcome these drawbacks, we introduce the Hybrid Firefly-Spotted Hyena Optimization (HFSHO) algorithm, a novel approach that combines the rapid exploration and global search abilities of the Firefly Algorithm (FO) with the localized search and region-exploitation skills of the Spotted Hyena Optimization Algorithm (SHO). HFSHO aims to improve logistics path optimization and reduce operational costs. The algorithm’s effectiveness is systematically assessed through rigorous comparative analyses… More >