Sustainable closed-loop supply chain network design: heuristic hybrid approach with considering inflation and carbon emission policies by Saeid Kalantari, Hamed Kazemipoor, Farzad Movahedi Sobhani, Seyyed Mohammad Hadji Molana

“…The findings showed that in different scenarios, the effective improvement of the obtained solutions by reducing the solution time by twenty percent could address large-scale problems.Originality/Value: By considering a new combined method of heuristic algorithm and multi-choice ideal programming with a utility function, this paper is done to solve the problem of designing a stable closed-loop supply chain network under uncertainty.…”
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ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space by Zhihui Chen, Ting Lan, Zhanchuan Cai, Zonglin Liu, Renzhang Chen

“…This paper proposes a novel improved crisscross optimization (ICSO) algorithm, a hybrid evolutionary approach that integrates crisscross optimization and perturbation mechanisms to find the suitable latent vector. …”
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Performance of machine learning algorithms to evaluate the physico-mechanical properties of nanoparticle panels by Derrick Mirindi, James Hunter, David Sinkhonde, Tajebe Bezabih, Frederic Mirindi

“…The Pearson correlation analysis reveals a strong relationship between board properties (R = 0.94 for WA–TS; R = 0.93 for MOR–MOE), confirming that nanoparticle treatments enhance performance while maintaining inherent material behavior. Hierarchical clustering grouped nanoparticles by performance: zinc oxide and chitosan+UF+epoxy formed a cluster with the lowest WA and TS, indicating optimal dimensional stability, while GO, rGO, and chitosan-based composites clustered with moderate values. …”
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LSTM-DQN-APF Path Planning Algorithm Empowered by Twins in Complex Scenarios by Ying Lu, Xiaodan Wang, Yang Yang, Man Ding, Shaochun Qu, Yanfang Fu

“…The results demonstrate that the LSTM-DQN-APF algorithm, combined with the digital twin platform, can significantly improve the issues of unreachable goals, local optimality, and real-time performance in UAV operations in complex environments. …”
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Optimal Design of Low Sidelobe Sparse Linear Arrays by Li Wang, Fenggan Zhang, Banghuan Hou

“…To optimize the antenna performance in a sparse linear array (SLA) subject to specific constraints of the antenna aperture, number of elements and element spacing, this paper proposes an improved Differential Evolution (DE) algorithm integrating the Cauchy-Gauss mutation strategy. …”
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A multi-objective optimized OLSR routing protocol. by Wenhong Wei, Huijia Wu, Ying He, Qingxia Li

“…In order to solve the problem that the better node set may not be selected when selecting the node set responsible for forwarding in the traditional OLSR protocol, a multi-objective optimized OLSR algorithm is proposed in this paper, which incorporating a new MPR mechanism and an improved NSGA-II algorithm. …”
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LEO multi-service routing algorithm based on multi-objective decision making by Li YANG, Jing SUN, Cheng-sheng PAN, Qi-jie ZOU

“…In low earth orbit(LEO) satellite networks,in view of the unbalanced link resource,it's difficult to meet differentiated quality of service(QoS) requirements and easily lead to reduce the efficiency of the whole network.A routing algorithm based on multi-objective decision making was proposed which defined LEO satellite network transmission service as the delay sensitive,sensitive bandwidth and reliability sensitive three categories.It used the eigenvector method to calculate service weights,and used the consistency ratio to determine whether it can be accepted.Based on the multi-objective decision making theory,it combined with the actual state of satellite network nodes and links and the specific requirements of the business,calculating the path that meets the QoS requirements of the service,so as to realize the LEO satellite network multi objective dynamic routing optimization.Established simulation platform based on the iridium network system simulated network delay,the uncertain characteristics like the residual bandwidth and packet error rate,route planning for the randomly generated three classes of business.The simulation results show that,the algorithm not only satisfies the QoS constrain while balancing the traffic load of the satellite link effectively,but also improves the performance on the throughput.…”
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Service chain deployment algorithms for deterministic end-to-end delay upper bound by Ze’nan WANG, Jiao ZHANG, Shuo WANG, Tao HUANG, F.Richard Yu

“…To solve the problem that the current service chain deployment algorithms cannot guarantee the delay of each packet passing through the service chain (SC), a SC deployment algorithm for deterministic end-to-end delay upper bound was proposed.First, the end-to-end delay bound of the SC was derived based on network calculus.Then, the deterministic end-to-end delay bound of the SC was achieved by collaboratively optimizing the routing of SC and the resource allocation of the virtual network function nodes in the SC.The experimental results show that the proposed algorithm can effectively improve the volume of accepted SC while guaranteeing that the end-to-end delay of each packet satisfies the delay requirements.…”
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Evolution of Cleft Lip and Palate Surgery and the Pursuit for Consensus on Standardized Algorithms of Care by Priyanka Naidu, MBChB, MS, Alexander T. Plonkowski, MBBS, MRes, Caroline A. Yao, MD, MS, William P. Magee, III, MD, DDS

“…Cleft lip and palate (CLP) surgery has evolved over centuries in an attempt to achieve anatomical closure while optimizing speech and limiting fistulas and midface hypoplasia. …”
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Enhancing the Harrow-Hassidim-Lloyd (HHL) algorithm in systems with large condition numbers by Peniel Bertrand Tsemo, Akshaya Jayashankar, K. Sugisaki, Nishanth Baskaran, Sayan Chakraborty, V. S. Prasannaa

“…In this work, we address the issue by introducing the postselection-improved HHL (Psi-HHL) framework that operates on a simple yet effective premise: subtracting mixed and wrong signals to extract correct signals while providing the benefit of optimal scaling in the condition number of A (denoted as κ) for large κ scenarios. …”
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Bilevel Optimization for ISAC Systems with Proactive Eavesdropping Capabilities by Tingyue Xue, Wenhao Lu, Mianyi Zhang, Yinghui He, Yunlong Cai, Guanding Yu

“…With the help of the proposed algorithm, we obtain the optimal solution of the analog transmit beamforming matrix and the digital beamforming vector. …”
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Fault location and isolation technology for power grid automation based on intelligent algorithms by Qi Guo, Fuhe Wang, Suxia Cheng, Ke Wang, Yifan Zhang

“…As power grids become more complex, intelligent algorithms are critical for improving the efficiency of fault localization and isolation. …”
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Automatic Vehicles’ Trajectories Optimization on Highway Exclusive Lanes by Lingjuan Chen, Yangbo Ruan, Yiquan Gou

“…The rapid development of V2X communication has made it possible to optimize and control the trajectories of vehicles from the whole traffic flow’s perspective and improve traffic performance. …”
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A Hybrid EV Charging Approach Based on MILP and a Genetic Algorithm by Syed Abdullah Al Nahid, Junjian Qi

“…This study underscores the potential of hybrid charging schemes in optimizing energy utilization while maintaining system reliability and user convenience.…”
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Vehicle Authentication-Based Resilient Routing Algorithm With Dynamic Task Allocation for VANETs by Nagaraju Pacharla, K. Srinivasa Reddy

“…With the goal of reducing task offloading delay and improving enhanced reaction time, a VANET-based task scheduling system is proposed after selecting an optimal route in the VANET. …”
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Optimizing Medical IoT Disaster Management with Data Compression by Nunudzai Mrewa, Athirah Mohd Ramly, Angela Amphawan, Tse Kian Neo

“…To tackle this issue, we introduce "Beyond Orion," a novel lossless compression method designed to optimize data compression in IoT systems. The algorithm employs advanced techniques such as Lempel Ziv-Welch and Huffman encoding, while also integrating strategies like pipelining, parallelism, and serialization for greater efficiency and lower resource usage. …”
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A Constrained Solution Update Strategy for Multiobjective Evolutionary Algorithm Based on Decomposition by Yuchao Su, Qiuzhen Lin, Jia Wang, Jianqiang Li, Jianyong Chen, Zhong Ming

“…This paper proposes a constrained solution update strategy for multiobjective evolutionary algorithm based on decomposition, in which each agent aims to optimize one decomposed subproblem. …”
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Research on an internal model control algorithm and parameter tuning for metro traction PMSMs by SI Junmin, YUE Xuelei, TIAN Di, XU Kelei

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Dynamic and adaptive multi-path routing algorithm based on software-defined network by Wu Jiawei, Qiao Xiuquan, Nan Guoshun

“…Moreover, our proposed algorithm can significantly reduce the computational overhead of the controller while completing a fine-grained flow balance. …”
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Implementation of Apriori Algorithm in Identifying Purchase Relationships at Bluder Cokro Pakuwon Mall by Angeline Ivana, Indra Maryati

“…These findings indicate that strategic product placement and bundling promotions can enhance sales performance. Optimizing the store layout by placing coklat keju near coklat can increase purchase likelihood, while targeted discounts, such as "Buy coklat keju, get 10% off keju," can drive transaction values. …”
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