Mathematics

The Capacitated Vehicle Routing Problem (CVRP) has a wide range of applications in logistics and transportation. Current metaheuristics typically rely on manually added constraints. A hyper-heuristic framework can reduce the dependency on domain-specific knowledge. Therefore, this research proposes a Clustered Simulated Annealing algorithm (CSA). When generating the initial solution of the distribution path, the CSA adopts the Clustered Clarke–Wright Savings algorithm (CCW), the core of which is to use the K-means algorithm to cluster according to the Euclidean distances between the distribution points. The CCW can reduce the search range of the optimization problem by clustering and generating the initial solution quickly, enabling the CSA to perform better in data processing and real-time updates. The CSA then optimizes the initial solution using the Improved Simulated Annealing Hyper-Heuristic algorithm (ISAHH), divided into upper and lower layers. The Improved Simulated Annealing High-Level Heuristic strategy (ISAHLH) is used to select the Low-Level Heuristic operators (LLHs). At the same time, LLHs are used to generate new distribution paths. This research designs an Improved Tabu Low-Level Heuristic operator (ITabuLLH), which can search for several different paths simultaneously in a single iteration, thus improving the convergence speed of the algorithm. ISAHLH and ITabuLLH both use the Unequal Probability Selection mode (UEPS) to speed up the search process. The CSA is tested on the Uchoa benchmark set, and the results verify that the optimal value improvement of the CSA solution is higher than 20% when compared to eleven other algorithms.

In industrial environments, providing intuitive spatial information via 3D maps is essential for maximizing the efficiency of teleoperation. However, existing SLAM algorithms generating 3D maps predominantly focus on improving robot localization accuracy, often neglecting the optimization of viewability required for human operators to clearly perceive object depth and structure in virtual environments. To address this, this study proposes a methodology to optimize the viewability of RTAB-Map-based 3D maps using the Taguchi method, aiming to enhance VR teleoperation efficiency and reduce cognitive workload. We identified eight key parameters that critically affect visual quality and utilized an L18 orthogonal array to derive an optimal combination that controls point cloud density and noise levels. Experimental results from a target object picking task demonstrated that the optimized 3D map reduced task completion time by approximately 9 s compared to the RGB image condition, achieving efficiency levels approaching those of the physical-world baseline. Furthermore, evaluations using NASA-TLX confirmed that intuitive visual feedback minimized situational awareness errors and substantially alleviated cognitive workload. This study suggests a new direction for constructing high-efficiency teleoperation interfaces from a Human–Robot Interaction perspective by expanding SLAM optimization criteria from geometric precision to user-centric visual quality.

A critical decision in pre-disaster humanitarian logistics planning is determining the amount of aid to preposition to ensure timely and effective emergency response. To support managers in this process, we propose four mathematical formulations designed to optimize food prepositioning and subsequent distribution while minimizing unmet demand under supply uncertainty. Two formulations adopt the cardinality-constrained approach: one focuses on minimizing unmet demand, and the other incorporates equity in meeting demand. The remaining two formulations are scenario-based, addressing the same objectives with and without equity considerations. To compare the variations in the solutions generated by the proposed formulations and gain a deeper understanding of their behavior and performance, the formulations are applied to synthetic instances. To assist managers in selecting the model that best aligns with their objectives, we provide a summary of the advantages and disadvantages of each formulation. Our results show that considering supply uncertainty has important implications for the total costs, and that having adequate storage capacity may help mitigate the problems caused by this uncertainty.