Total Tardiness Minimization in a Single-Machine with Periodical Resource Constraints by Bruno Prata, Levi Ribeiro de Abreu, Marcelo Seido Nagano

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Hysteresis in Combinatorial Optimization Problems by Yuling Guan, Ang Li, Sven Koenig, Stephan Haas, T. K. Satish Kumar

“…Our WCSP framework also allows us to understand hysteresis more generally in combinatorial optimization problems, with or without a connection to physically occurring phenomena.…”
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Electric Vehicle Routing Problem with Heterogeneous Energy Replenishment Infrastructures Under Capacity Constraints by Bowen Song, Rui Xu

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Robust Combinatorial Optimization with Locally Budgeted Uncertainty by Goerigk, Marc, Lendl, Stefan

“…Budgeted uncertainty sets have been established as a major influence on uncertainty modeling for robust optimization problems. A drawback of such sets is that the budget constraint only restricts the global amount of cost increase that can be distributed by an adversary. …”
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Inductive Construction of Variational Quantum Circuit for Constrained Combinatorial Optimization by Hyakka Nakada, Kotaro Tanahashi, Shu Tanaka

“…Recently, several methods for efficiently solving constrained combinatorial optimization problems have been proposed by designing a quantum circuit so as to output only the states that satisfy the constraints. …”
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Quick design of feasible tensor networks for constrained combinatorial optimization by Hyakka Nakada, Kotaro Tanahashi, Shu Tanaka

“…Particularly, tensor networks have been applied to constrained combinatorial optimization problems for practical applications. …”
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Combinatorial Robust Optimization with Decision-Dependent Information Discovery and Polyhedral Uncertainty by Omer, Jérémy, Poss, Michael, Rougier, Maxime

“…Given a nominal combinatorial optimization problem, we consider a robust two-stages variant with polyhedral cost uncertainty, called Decision-Dependent Information Discovery (DDID). …”
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UAV mission scheduling with completion time, flight distance, and resource consumption constraints by Keqin Li

“…Furthermore, UAV task scheduling should be studied within the traditional framework of combinatorial optimisation. In this paper, we consider optimal mission scheduling for heterogeneous UAVs with completion time, flight distance, and resource consumption constraints. …”
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Reinforcement Learning-Based Formulations With Hamiltonian-Inspired Loss Functions for Combinatorial Optimization Over Graphs by Redwan Ahmed Rizvee, Raheeb Hassan, Md. Mosaddek Khan

“…Quadratic Unconstrained Binary Optimization (QUBO) is a versatile approach used to represent a wide range of NP-hard Combinatorial Optimization (CO) problems through binary variables. …”
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Combinatorial Optimization of Service Order and Overtaking for Demand-Oriented Timetabling in a Single Railway Line by Dewei Li, Shishun Ding, Yizhen Wang

“…Demand-oriented train timetable optimization by minimizing travel time plays an important role in both theory and practice. …”
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Improved ant colony optimization algorithm for solving constraint satisfaction problem by HANGYong-gang Z, HANGSi-bo Z, UEQiu-shi X

“…The traditional backtracking algorithm was less efficient on solving large-scale constraint satisfaction problem,and more difficult to be solved within a reasonable time.In order to overcome this problem,many incompleteness algo-rithms based on heuristic search have been proposed.Two improvements based on ant colony optimization meta-heuristic constraint solving algorithm were presented:First,arc consistency checks was done to preprocess before exploring the search space,Second,a new parameter setting scheme was proposed for ant colony optimization to improve the effi-ciency of the search.Finally,the improved algorithm is applied to solve random problems and combinatorial optimization problems.The results of the experiment have showed its superiority.…”
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Quantum-Inspired Hyperheuristic Framework for Solving Dynamic Multi-Objective Combinatorial Problems in Disaster Logistics by Kassem Danach, Hassan Harb, Louai Saker, Ali Raad

“…In this context, we propose a novel Quantum-Inspired Hyperheuristic Framework (QHHF) designed to solve Dynamic Multi-Objective Combinatorial Optimization Problems (DMOCOPs) arising in disaster relief operations. …”
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Forgetful Swarm Optimization for Astronomical Observation Scheduling by Nariman Nakhjiri, Maria Salamo, Miquel Sanchez-Marre, Christian Blum, Juan Carlos Morales

“…In this paper, we propose a novel metaheuristic algorithm called Forgetful Swarm Optimization (FSO) for Astronomical Observation Scheduling (AOS), a type of combinatorial optimization problem defined by the tasks and constraints assigned to the telescopes and other devices involved in astrophysical research. …”
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Cons-training tensor networks: Embedding and optimization over discrete linear constraints by Javier Lopez-Piqueres, Jing Chen

“…Utilizing this canonical form, we apply an unsupervised training strategy to optimize arbitrary objective functions subject to discrete linear constraints. …”
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Limitations of quantum approximate optimization in solving generic higher-order constraint-satisfaction problems by Thorge Müller, Ajainderpal Singh, Frank K. Wilhelm, Tim Bode

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Robust Optimization for Cooperative Task Assignment of Heterogeneous Unmanned Aerial Vehicles with Time Window Constraints by Zhichao Gao, Mingfa Zheng, Haitao Zhong, Yu Mei

“…We conduct a series of numerical experiments to compare the optimization results across different objectives, including maximizing task profit, minimizing total distance, minimizing makespan, and incorporating three different time window constraints. …”
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Optimal Conflict Resolution for Vehicles With Intersecting and Overlapping Paths by Johan Karlsson, Nikolce Murgovski, Jonas Sjoberg

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A Biased–Randomized Iterated Local Search with Round-Robin for the Periodic Vehicle Routing Problem by Juan F. Gomez, Antonio R. Uguina, Javier Panadero, Angel A. Juan

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Efficient Multi-Target Localization Using Dynamic UAV Clusters by Wei Gong, Shuhan Lou, Liyuan Deng, Peng Yi, Yiguang Hong

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Population-Based Redundancy Control in Genetic Algorithms: Enhancing Max-Cut Optimization by Yong-Hyuk Kim, Zong Woo Geem, Yourim Yoon

“…The max-cut problem is a well-known topic in combinatorial optimization, with a wide range of practical applications. …”
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