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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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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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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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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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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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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PROBLEM OF OPTIMAL CONTROL OF EPIDEMIC IN VIEW OF LATENT PERIOD by N. I. Ovsyannikova

“…The problem of optimal control of epidemic through vaccination and isolation, taking into account latent period is considered. …”
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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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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

“…This problem is subsequently solved using an enhanced column-and-constraint generation (C&CG) algorithm with adaptive cut generation. …”
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Proactive Scheduling and Routing of MRP-Based Production with Constrained Resources by Jarosław Wikarek, Paweł Sitek

“…The lack of seamless integration between customer orders and production tasks, combined with the manual and time-consuming nature of schedule adjustments, highlights the need for an automated and optimized scheduling method. We propose a novel optimization-based approach that leverages mixed-integer linear programming (MILP) combined with a proprietary procedure for reducing the size of the modeled problem to generate feasible and/or optimal production schedules. …”
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Interdisciplinary Methodology for Resource Allocation Problems Using Artificial Neural Networks and Software Robots by Marta Lilia Erana-Diaz, Marco Antonio Cruz-Chavez, Mario Acosta-Flores, Juana Enriquez-Urbano, Nadia Lara Ruiz, Jorge Pablo Oseguera Gamba

“…By considering psychosocial and productivity factors in the optimization model, the study moves beyond traditional methods that often prioritize efficiency at the expense of human considerations. …”
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Optimal information dissemination strategy to promote preventivebehaviors in multilayer epidemic networks by Heman Shakeri, Faryad Darabi Sahneh, Caterina Scoglio, Pietro Poggi-Corradini, Victor M. Preciado

“…Inherent differences between these two layers cause alerting through CN to be more effective but more expensive than IDN. The constraint for an epidemic to die out derived from a nonlinear Perron-Frobenius problem that was transformed into a semi-definite matrix inequality and served as a constraint for a convex optimization problem. …”
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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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Optimizing Container Repositioning Using a Sequential Insertion Algorithm for Pickup-Delivery Routing in Export-Import Operations by Ary Arvianto, Dihan Chofifah Cahyani, Dhimas Wachid Nur Saputra

“…The increasing number of empty containers significantly causes to traffic congestion and rising operational costs, thereby necessitating the development of an optimized routing model to enhance fleet utilization and minimize transportation expenses. …”
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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

“…To solve this complex optimization problem, a hybrid algorithm combining genetic algorithms and particle swarm optimization was designed. …”
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A Model for Bus Crew Scheduling Problem with Multiple Duty Types by Mingming Chen, Huimin Niu

“…An optimization model is formulated as a 0-1 integer programming problem to improve the efficiency of crew scheduling at the minimum expense of total idle time of crew for a circle bus line. …”
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Deep Reinforcement Learning with Local Attention for Single Agile Optical Satellite Scheduling Problem by Zheng Liu, Wei Xiong, Chi Han, Xiaolan Yu

“…Owing to the complicated constraints and considerable solution space of this problem, the conventional exact methods and heuristic methods, which are sensitive to the problem scale, demand high computational expenses. …”
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Parallel Primal-Dual Method with Linearization for Structured Convex Optimization by Xiayang Zhang, Weiye Tang, Jiayue Wang, Shiyu Zhang, Kangqun Zhang

“…This paper presents the Parallel Primal-Dual (PPD3) algorithm, an innovative approach to solving optimization problems characterized by the minimization of the sum of three convex functions, including a Lipschitz continuous term. …”
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