Surrogate-assisted global and distributed local collaborative optimization algorithm for expensive constrained optimization problems by Xiangyong Liu, Zan Yang, Jiansheng Liu, Junxing Xiong, Jihui Huang, Shuiyuan Huang, Xuedong Fu

“…Abstract This paper presents a surrogate-assisted global and distributed local collaborative optimization (SGDLCO) algorithm for expensive constrained optimization problems where two surrogate optimization phases are executed collaboratively at each generation. …”
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A Preference Model-Based Surrogate-Assisted Constrained Multi-Objective Evolutionary Algorithm for Expensively Constrained Multi-Objective Problems by Yu Sun, Yifan Ma, Bei Hua

“…In the context of expensive constraint multi-objective problems, it is evident that the feasible domain shapes and sizes of different problems vary considerably. …”
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Computationally expensive constrained problems via surrogate-assisted dynamic population evolutionary optimization by Zan Yang, Chen Jiang, Jiansheng Liu

“…Abstract This paper proposes a surrogate-assisted dynamic population optimization algorithm (SDPOA) for the purpose of solving computationally expensive constrained optimization problems, in which the population is dynamically updated based on the real-time iteration information to achieve targeted searches for solutions with different qualities. …”
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Constrained Bayesian Optimization: A Review by Sasan Amini, Inneke Vannieuwenhuyse, Alejandro Morales-Hernandez

“…Bayesian optimization is a sequential optimization method that is particularly well suited for problems with limited computational budgets involving expensive and non-convex black-box functions. …”
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State information-driven surrogate-assisted differential evolution for computationally expensive constrained optimization problems by Zihua Zhu, Zan Yang, Zhiyong Liu, Liming Chen, Xiwen Cai

“…Abstract In this paper, a state information-driven surrogate-assisted differential evolution called SI-SADE is proposed for solving expensive constrained optimization problems, in which both the population state and adaptive search mechanism are respectively evaluated and designed based on the feasibility and state information. …”
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Optimization of the structure of the learning process under the given constraints by A. A. Lobaty, D. A. Konopacki

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Time-Optimal Stabilization of Asynchronous Boolean Control Networks Under State and Control Constraints by Haonan Wang, Shuping Wang, Ruohai Xi, Shuhua Gao

“…This paper investigates the problem of time-optimal stabilization in Boolean control networks (BCNs) with an asynchronous update scheme, subject to state and control constraints. …”
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Supply–Demand Dynamics Quantification and Distributionally Robust Scheduling for Renewable-Integrated Power Systems with Flexibility Constraints by Jiaji Liang, Jinniu Miao, Lei Sun, Liqian Zhao, Jingyang Wu, Peng Du, Ge Cao, Wei Zhao

“…The optimization objective aims to minimize total operational costs, encompassing resource activation expenses and flexibility deficit penalties. …”
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Proactive Scheduling and Routing of MRP-Based Production with Constrained Resources by Jarosław Wikarek, Paweł Sitek

“…By automating the generation of data from MRP/ERP systems, constructing an optimization model, and exporting the results back to the MRP/ERP structure, this method improves decision-making and competes with expensive Advanced Planning and Scheduling (APS) systems. …”
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Integrating source-sink coordination and pod-setting optimization: A field study on plant density effects for soybean productivity enhancement in the Huang-Huai-Hai Plain by Lei Yang, Xiaofei Chen, Wenjun Jin, Jie Zhou, Yi Xu, Ruixian Liu, Wenwen Song, Lingcong Kong, Zhiping Huang, Xiangbei Du

“…Beyond 315,000 plants ha−1, however, seeds per m2 and 100-seed weight declined despite continued increases in plant height, LAI, and LIR, signaling a shift in photoassimilate allocation to stems and leaves at the expense of yield sinks. These findings highlight a transition from source-limited to sink-limited yield constraints as PD rises. …”
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Optimizing appliance scheduling for utility and budget in smart energy systems under inclining block rate tariffs by Ahmed Shaban, Mohamed Salhen, Mohamed A. Shalaby, Tamer F. Abdelmaguid

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Finding the Shortest Path with Vertex Constraint over Large Graphs by Yajun Yang, Zhongfei Li, Xin Wang, Qinghua Hu

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Novel method to measure track irregularity based on multiple MEMS-IMU and geometric constraint by Yan Wang, Shibin Wei, Lin Li, Jiyou Fei, Fei Yang, Peng Dai

“…To achieve this, we first construct the geometric constraint models for multiple MEMS-IMUs and establish their optimal installation configuration. …”
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Daily life in Bassarabia in the 1930s: income and expenditures of the local population by Aurel Fondos

“…Even so, the possibilities of living gathered in this way are so small that they hardly cover the basic needs of the inhabitants. Financial constraints are also attested at the level of local institutions in Bassarabia, which have led to cost reductions and optimizations. …”
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A cost-effective image-based model without constraint for weight estimation of poultries using deep learning by Zhi Qiao, Jianhui Liu, Fangxi Yang, Jinping Hao, Zhuocheng Hou, Hui Li, Feng Zhu

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Service Management of Employee Shuttle Service Under Inhomogeneous Fleet Constraints Using Dynamic Linear Programming: A Case Study by Metin Mutlu Aydin, Edgar Sokolovskij, Piotr Jaskowski, Jonas Matijošius

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Research on Multi-Center Path Optimization for Emergency Events Based on an Improved Particle Swarm Optimization Algorithm by Zeyu Zou, Hui Zeng, Xiaodong Zheng, Junming Chen

“…In the initial stages of an emergency, decision-makers face the dual challenge of minimizing transportation costs while adhering to stringent rescue time constraints. To address these issues, this study proposes a two-stage optimization model aimed at ensuring the equitable distribution of disaster relief materials across multiple distribution centers. …”
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NCREASING ECONOMIC PERFORMANCES USING OPTIMIZATION by Daniela-Elena ȘURCĂ

“…The optimization process was accomplished by using a mathematical model of linear programming consisting of variables, constants, constraints and objective function. …”
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A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems by Mohamed H. ElMessmary, Hatem Y. Diab, Mahmoud Abdelsalam, Mona F. Moussa

“…One of the most important issues that can significantly affect the electric power network’s ability to operate sustainably is the optimal power flow (OPF) problem. It involves reaching the most efficient operating conditions for the electrical networks while maintaining reliability and systems constraints. …”
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ADPO: Adaptive DRAM Controller for Performance Optimization by Zhuorui Liu, Yan Li, Xiaoyang Zeng

“…However, under the stringent physical constraints of chip packages and system boards, it is extremely expensive to further increase the bandwidth and reduce the dynamic loaded latency of off-chip memory in terms of DDR devices. …”
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