Multi-Depot Pickup and Delivery Problem with Resource Sharing by Yong Wang, Lingyu Ran, Xiangyang Guan, Yajie Zou

“…Resource sharing (RS) integrated into the optimization of multi-depot pickup and delivery problem (MDPDP) can greatly reduce the logistics operating cost and required transportation resources by reconfiguring the logistics network. …”
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Multi-objective artificial-intelligence-based parameter tuning of antennas using variable-fidelity machine learning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Stanislaw Szczepanski

“…Due to the reliance on computationally-expensive electromagnetic (EM) simulations, the use of conventional algorithms is prohibitive. These costs can be reduced by appropriate algorithmic tools involving surrogate modeling and soft computing methods. …”
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Performance evaluation of an adopted model based on big-bang big-crunch and artificial neural network for cloud applications by Pradeep Rawat, Robin Singh Bhadoria, Punit Gupta, Priti Dimri, G. P. Saroha

“…Cloud can accomplish this using efficient scheduling algorithm. This article focuses on task scheduling policy which aims to improve the performance in real-time with the least execution time, network cost and execution cost-effective at the same time. …”
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Robust collaborative mesh networking with large-scale distributed wireless heterogeneous terminals in industrial cyber-physical systems by Tao Wang, Jun Liu, Lianglun Cheng, Hong Xiao

“…Second, the robustness-aware collaborative mesh networking problem is formulated with a multi-objective optimization model, and an improved multi-objective particle swarm optimization algorithm based on self-adaptive evolutionary learning is exploited to search out the Pareto optimal particles with better distribution and diversity. …”
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Subspace-based local compilation of variational quantum circuits for large-scale quantum many-body simulation by Shota Kanasugi, Yuichiro Hidaka, Yuya O. Nakagawa, Shoichiro Tsutsui, Norifumi Matsumoto, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

“…The optimization is performed for small local subsystems based on the Lieb-Robinson bound, which allows us to execute the cost function evaluation using small-scale quantum devices and/or classical computers. …”
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Double-layer energy transaction strategy of multi-microgrids and distribution network with leased shared energy storage by WANG Hui, WU Zuohui, LI Xin, ZOU Zhichao, ZHOU Kerui

“…In profit allocation of microgrid alliance, an asymmetric Nash bargaining method is proposed that fairly distribute profits according to the contribution size of each member in providing energy. Finally, an improved particle swarm optimization algorithm combined with the alternating direction multiplier method is adopted to solve the hybrid game model. …”
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Reoptimization Heuristic for the Capacitated Vehicle Routing Problem by Rodrigo Linfati, John Willmer Escobar

“…Next, the local search procedure is executed to improve the solution. A classic optimization is performed on all instances using the original and new customers’ information for later comparison to minimize distance. …”
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Multi-phase simultaneous segmentation of tumor in lung 4D-CT data with context information. by Zhengwen Shen, Zhengwen Shen, Huafeng Wang, Weiwen Xi, Xiaogang Deng, Jin Chen, Yu Zhang

“…In this paper, we propose a new method based on an improved graph cut algorithm with context information constraint to find a convenient and robust approach of lung 4D-CT tumor segmentation. …”
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Reliability-Based Opportunistic Maintenance Modeling for Multi-Component Systems with Economic Dependence under Base Warranty by Rongcai Wang, Zhonghua Cheng, Enzhi Dong, Chiming Guo, Liqing Rong

“…A simulated annealing (SA) algorithm is proposed to determine the optimal maintenance cost of the system and the optimal OM threshold under BW. …”
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Advanced day-ahead scheduling of HVAC demand response control using novel strategy of Q-learning, model predictive control, and input convex neural networks by Rahman Heidarykiany, Cristinel Ababei

“…More specifically, new input convex long short-term memory (ICLSTM) models are employed to predict dynamic states in an MPC optimal control technique integrated within a Q-Learning reinforcement learning (RL) algorithm to further improve the learned temporal behaviors of nonlinear HVAC systems. …”
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Agricultural Model for Allocation of Crops Using Pollination Intelligence Method by C. N. Ejieji, A. E. Akinsunmade

“…An improved version of the Flower Pollinated Algorithm called Pollination Intelligence Algorithm using an iterative scheme to override the switch parameter in Flower Pollinated Algorithm is also presented and used in solving the designed model. …”
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Wireless-powered cooperative energy aware anycast routing in wireless sensor networks by Fazle Hadi, Sheeraz Ahmed, Abid Ali Minhas, Abdulaziz Al Mazyad, Najam ul Islam, Imran Ahmed, Nadeem Javaid

“…Results further reveal that our proposed algorithm has improved energy consumption in comparison to the non-cooperative energy aware anycast scheme and the cooperation-based robust cooperative routing protocol scheme. …”
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Interfered feature elimination coupled with feature group selection for wound infection detection by electronic nose. by Jia Liu, Jinglei Zhang, Shaoqi Zhang, Kaiwei Li, Xiang Li, Shuo Zhang, Hang Gu, Zhen Chen, Chao Liu, Nan Zhang, Tong Sun

“…As the precise odor-sensing equipment, the electronic nose integrates multiple advanced and sensitive sensors that can identify wound infections non-invasively and rapidly by analyzing wound characteristic odor. To reduce the cost of sensors and improve or maintain e-nose's performance, efficient optimization of sensor arrays is required. …”
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A performance enhanced distributed computing framework for clustering by local direction centrality upon Apache Spark by Zhipeng Gui, Zichen Huang, Huan Chen, Dehua Peng, Yuhang Liu, Guangyao Fang, Qianxi Lan, Anqi Zhao, Huayi Wu

“…To improve its computational efficiency and scalability, we proposed a performance enhanced distributed framework of CDC, named D-CDC, by workflow-level algorithm optimization and distributed computational acceleration. …”
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Economic sizing and placement of hydrogen fueling and electric vehicles charging stations powered by renewable and battery systems in smart distribution network by Mehdi Veisi

“…Its goal is to minimize the sum of annual energy losses and operation costs within the grid, governed by linearized optimal power flow model. …”
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Distributed Multi-Energy Trading in Energy Internet: An Aggregative Game Approach by Jingwei Hu, Enhui An, Qiuye Sun, Bonan Huang

“…Since each WE only needs to communicate with its neighbors to exchange information, this distributed process reduces communication burden and improves information security. Furthermore, a multi-energy transmission optimization model is established to determine the transmission path of the transmission energy, which can minimize the transmission cost. …”
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A multi-objective metaheuristic method for node placement in dynamic IoT environments by Farzad Kiani

“…Abstract This study introduces an optimal Node Placement based on Enhanced Sand Cat Swarm Optimization (NP-ESCSO) algorithm, a novel metaheuristic approach for solving the node placement problem in dynamic IoT environments. …”
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Investigation on Photovoltaic Array Modeling and the MPPT Control Method under Partial Shading Conditions by Jianbo Bai, Leihou Sun, Rupendra Kumar Pachauri, Guangqing Wang

“…The experimental results show that the PV optimizer improves the output power of the PV modules by 13.4% under the PSC.…”
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Building Information Modelling- (BIM-) Based Generative Design for Drywall Installation Planning in Prefabricated Construction by Jose Daniel Cuellar Lobo, Zhen Lei, Hexu Liu, Hong Xian Li, SangHyeok Han

“…The framework includes a decision support module that considers environmental, cost, and aesthetic aspects to identify the optimal layout. …”
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Embedded Hardware-Efficient FPGA Architecture for SVM Learning and Inference by B. B. Shabarinath, Muralidhar Pullakandam

“…While Sequential Minimal Optimization (SMO) has enhanced the efficiency of SVM training, traditional implementations still suffer from high computational cost. …”
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