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An $$L_2$$ regularization reduced quadratic surface support vector machine model J. Comb. Optim. (IF 0.9) Pub Date : 2025-02-18 Jiguang Wang, Fangfang Guo, Jie Shen
In this paper, a reduced quadratic surface support vector machine (RQSSVM) classification model is proposed and solved using the augmented Lagrange method. The new model can effectively handle nonlinearly separable data without kernel function selection and parameter tuning due to its quadratic surface segmentation facility. Meanwhile, the maximum margin term is replaced by an \(L_2\) regularization
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A fuzzy approach for the intuitionistic multi-objective linear fractional programming problem using a bisection method J. Comb. Optim. (IF 0.9) Pub Date : 2025-02-09 Nurdan Kara, Hale Gonce Kocken, Hande Günay Akdemir
In this paper, intuitionistic fuzzy multi-objective linear fractional programming problems (IFMOLFPs) with several fractional criteria, including profit/cost, profit/time, or profitability ratio maximization, are considered. Moreover, all parameters, with the exception of the decision variables, are characterized as triangular intuitionistic fuzzy numbers. The component-wise optimization method is
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Embedded-filter ACO using clustering based mutual information for feature selection J. Comb. Optim. (IF 0.9) Pub Date : 2025-02-09 S. Kumar Reddy Mallidi, Rajeswara Rao Ramisetty
The performance of machine learning algorithms is significantly influenced by the quality of the underlying dataset, which often comprises a mix of essential and redundant features. Feature selection, which identifies and discards these redundant features, plays a pivotal role in reducing computational and storage overheads. Current methodologies for this task primarily span filter-based and wrapper-based
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Solving the optimal order quantity with unknown parameters for products with stock-dependent demand and variable holding cost rate J. Comb. Optim. (IF 0.9) Pub Date : 2025-02-09 Zhanbing Guo, Yejie Zhang
Solving the optimal order quantity for products with stock-dependent demand is a challenging task as both exact values of multiple parameters and complicated procedures are required. Motivated by this practical dilemma, this paper develops a new method to overcome the above-mentioned two challenges simultaneously. This new method, referred as two-stage AEOQ (adaptive economic order quantity) policy
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Recognizing integrality of weighted rectangles partitions J. Comb. Optim. (IF 0.9) Pub Date : 2025-01-20 Paul Deuker, Ulf Friedrich
Given a grid of active and inactive pixels, the weighted rectangles partitioning (WRP) problem is to find a maximum-weight partition of the active pixels into rectangles. WRP is formulated as an integer programming problem and instances with an integral relaxation polyhedron are characterized by a balanced problem matrix. A complete characterization of these balanced instances is proved. In addition
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An improved PTAS for covering targets with mobile sensors J. Comb. Optim. (IF 0.9) Pub Date : 2025-01-20 Nonthaphat Wongwattanakij, Nattawut Phetmak, Chaiporn Jaikaeo, Jittat Fakcharoenphol
This paper considers a movement minimization problem for mobile sensors. Given a set of n point targets, the k-Sink Minimum Movement Target Coverage Problem is to schedule mobile sensors, initially located at k base stations, to cover all targets minimizing the total moving distance of the sensors. We present a polynomial-time approximation scheme for finding a \((1+\epsilon )\) approximate solution
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Degree and betweenness-based label propagation for community detection J. Comb. Optim. (IF 0.9) Pub Date : 2025-01-20 Qiufen Ni, Jun Wang, Zhongzheng Tang
Community detection, as a crucial network analysis technique, holds significant application value in uncovering the underlying organizational structure in complex networks. In this paper, we propose a degree and betweenness-based label propagation method for community detection (DBLPA). First, we calculate the importance of each node by combining node degree and betweenness centrality. A node i is
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The undirected optical indices of trees J. Comb. Optim. (IF 0.9) Pub Date : 2025-01-20 Yuan-Hsun Lo, Hung-Lin Fu, Yijin Zhang, Wing Shing Wong
For a connected graph G, an instance I is a set of pairs of vertices and a corresponding routing R is a set of paths specified for all vertex-pairs in I. Let \(\mathfrak {R}_I\) be the collection of all routings with respect to I. The undirected optical index of G with respect to I refers to the minimum integer k to guarantee the existence of a mapping \(\phi :R\rightarrow \{1,2,\ldots ,k\}\), such
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$$(K_{1}\vee {P_{t})}$$ -saturated graphs with minimum number of edges J. Comb. Optim. (IF 0.9) Pub Date : 2025-01-20 Jinze Hu, Shengjin Ji, Qing Cui
For a fixed graph F, a graph G is F-saturated if G does not contain F as a subgraph, but adding any edge in \(E(\overline{G})\) will result in a copy of F. The minimum size of an F-saturated graph of order n is called the saturation number of F, denoted by sat(n, F). In this paper, we are interested in saturation problem of graph \(K_1\vee {P_t}\) for \(t\ge 2\). As some known results, \(sat(n,K_1\vee
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Agent-constrained truthful facility location games J. Comb. Optim. (IF 0.9) Pub Date : 2025-01-20 Argyrios Deligkas, Mohammad Lotfi, Alexandros A. Voudouris
We consider a truthful facility location game in which there is a set of agents with private locations on the line of real numbers, and the goal is to place a number of facilities at different locations chosen from the set of those reported by the agents. Given a feasible solution, each agent suffers an individual cost that is either its total distance to all facilities (sum-variant) or its distance
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Advertising meets assortment planning: joint advertising and assortment optimization under multinomial logit model J. Comb. Optim. (IF 0.9) Pub Date : 2025-01-20 Chenhao Wang, Yao Wang, Shaojie Tang
Despite the assortment optimization problem has been widely studied in the past decades, the interplay between advertising and its implications for this issue remains under-explored. This study seeks to bridge this research gap by tackling the combined challenge of advertising and assortment optimization. We assume that advertising can increase the awareness of specific products, and the magnitude
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Social media actors: perception and optimization of influence across different types J. Comb. Optim. (IF 0.9) Pub Date : 2025-01-20 Alexander A. Kharlamov, Aleksey N. Raskhodchikov, Maria Pilgun
The paper deals with the analysis of the communicative behavior of various types of actors, speech perception and optimization of influence based on social media data and is an extended version of the report presented at CSoNet 2020 and published based on the deliverables of the conference. The paper proposes an improved methodology that is tested on the new material of conflicts regarding urban planning
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Optimal dispatching of electric vehicles based on optimized deep learning in IoT J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-26 V. Agalya, M. Muthuvinayagam, R. Gandhi
Recent years have witnessed a growing trend in the utilization of Electric Vehicles (EVs), however with the increased usage of EVs, appropriate strategies for supporting the charging demands has not garnered much attention. The absence of adaptable plans in charging may result in minimized participation; further, the charging demands have to be addressed with utmost care for ensuring reliability and
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Lollipop and cubic weight functions for graph pebbling J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-25 Marshall Yang, Carl Yerger, Runtian Zhou
Given a configuration of pebbles on the vertices of a graph G, a pebbling move removes two pebbles from a vertex and puts one pebble on an adjacent vertex. The pebbling number of a graph G is the smallest number of pebbles required such that, given an arbitrary initial configuration of pebbles, one pebble can be moved to any vertex of G through some sequence of pebbling moves. Through constructing
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Discrete circles: analytical definition and generation in the hexagonal grid J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-19 Rita Zrour, Lidija Čomić, Eric Andres, Gaëlle Largeteau Skapin
We propose an analytical definition of discrete circles in the hexagonal grid. Our approach is based on a non-constant thickness function. We determine the thickness using the (edge and vertex) flake model. Both types of circles are connected. We prove that edge flake circles are without simple points for integer radii. Incremental generation algorithms are deduced from the analytical characterization
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Optimal blocks for maximizing the transaction fee revenue of Bitcoin miners J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-19 Mohsen Alambardar Meybodi, Amir Goharshady, Mohammad Reza Hooshmandasl, Ali Shakiba
In this work, we consider a combinatorial optimization problem with direct applications in blockchain mining, namely finding the most lucrative blocks for Bitcoin miners, and propose optimal algorithmic solutions. Our experiments show that our algorithms increase the miners’ revenues by more than a million dollars per month. Modern blockchains reward their miners in two ways: (i) a base reward for
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Facial expression-based emotion recognition across diverse age groups: a multi-scale vision transformer with contrastive learning approach J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-16 G. Balachandran, S. Ranjith, T. R. Chenthil, G. C. Jagan
Facial expression-based Emotion Recognition (FER) is crucial in human–computer interaction and affective computing, particularly when addressing diverse age groups. This paper introduces the Multi-Scale Vision Transformer with Contrastive Learning (MViT-CnG), an age-adaptive FER approach designed to enhance the accuracy and interpretability of emotion recognition models across different classes. The
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Online multiple one way non-preemptive time series search with interrelated prices J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-16 Jinghan Zhao, Yongxi Cheng, Jan Eube, Haodong Liu
This paper studies the online multiple time series search problem with interrelated prices (MTSS-ip). This perspective narrows the distance between the problem and the reality of market prices with limited variation. In MTSS-ip, the products arrive periodically, and the decision maker has a limited storage size without knowing future prices. The prices of two adjacent periods are interrelated. This
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Spectral influence in networks: an application to input-output analysis J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-16 Nizar Riane
This paper introduces the concepts of spectral influence and spectral cyclicality, both derived from the largest eigenvalue of a graph’s adjacency matrix. These two novel centrality measures capture both diffusion and interdependence from a local and global perspective respectively. We propose a new clustering algorithm that identifies communities with high cyclicality and interdependence, allowing
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Np-completeness and bounds for disjunctive total domination subdivision J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-14 Canan Çiftçi, Aysun Aytaç
A subset \( S\subseteq V(G) \), where V(G) is the vertex set of a graph G, is a disjunctive total dominating set of G if each vertex has a neighbour in S or has at least two vertices in S at distance two from it. The minimum cardinality of such a set is the disjunctive total domination number. There are some graph modifications on the edge or vertex of a graph, one of which is subdividing an edge.
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A study on $$k$$ - $$walk$$ generation algorithm to prevent the tottering in graph edit distance heuristic algorithms J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-07 SeongCheol Yoon, Daehee Seo, Su-Hyun Kim, Im-Yeong Lee
Graph edit distance is usually used for graph similarity checking due to its low information loss and flexibility advantages. However, graph edit distance can’t be used efficiently because it is an NP-Hard problem. Many graph edit distance heuristic algorithms have been proposed to solve this problem. However, some heuristic algorithms for generating \(walk\) generate unnecessary sequences because
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New bounds on the price of anarchy of selfish bin packing with partial punishment J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-04 Xiaowei Li, Peihai Liu, Xiwen Lu
The selfish bin packing with partial punishment is studied in this paper. In this problem, the utility of an item is defined as the load of the bin it is in. Each item plays the role of a selfish agent and wants to maximize its own utility. If an item with size \(s_i\) moves to another bin, it has to pay the partial punishment of \(\alpha s_{i}\), where \(0<\alpha <1\). We prove that the price of anarchy
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Customer segmentation using flying fox optimization algorithm J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-04 Konstantinos Zervoudakis, Stelios Tsafarakis
Customer segmentation, a critical strategy in marketing, involves grouping consumers based on shared characteristics like age, income, and geographical location, enabling firms to effectively establish different strategies depending on the target group of customers. Clustering is a widely utilized data analysis technique that facilitates the identification of diverse groups, each distinguished by their
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Online scheduling on an unbounded parallel-batch machine to minimize the weighted makespan J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-04 Han Zhang, Lingfa Lu, Jinjiang Yuan
In this paper we study the online over-time scheduling on an unbounded parallel-batch machine to minimize the weighted makespan. First, we show that the general problem has a low bound 2 and then design a 4-competitive online algorithm. Furthermore, we consider a special case in which the jobs have agreeable processing times and weights. When all jobs have the same weights (the task is to minimize
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Greedy algorithms for stochastic monotone k-submodular maximization under full-bandit feedback J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-04 Xin Sun, Tiande Guo, Congying Han, Hongyang Zhang
In this paper, we theoretically study the Combinatorial Multi-Armed Bandit problem with stochastic monotone k-submodular reward function under full-bandit feedback. In this setting, the decision-maker is allowed to select a super arm composed of multiple base arms in each round and then receives its k-submodular reward. The k-submodularity enriches the application scenarios of the problem we consider
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Approximation algorithms for the airport and railway problem J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-04 Mohammad R. Salavatipour, Lijiangnan Tian
In this paper, we present approximation algorithms for the Airport and Railway problem (AR) on several classes of graphs. The \(\text{ AR }\) problem, introduced as reported by Adamaszek et al. (in: Ollinger, Vollmer (eds) 33rd symposium on theoretical aspects of computer science (STACS 2016). Leibniz international proceedings in informatics (LIPIcs), Dagstuhl, 2016), is a combination of the Capacitated
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Incentive mechanism design for value-decreasing tasks in dynamic competitive edge computing networks J. Comb. Optim. (IF 0.9) Pub Date : 2024-12-03 Qie Li, Zichen Wang, Hongwei Du
With the rapid development of network architectures and application technologies, there is an increasing number of latency-sensitive tasks generated by user devices, necessitating real-time processing on edge servers. During peak periods, user devices compete for limited edge resources to execute their tasks, while different edge servers also compete for transaction opportunities. This article focus
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Enhanced deterministic approximation algorithm for non-monotone submodular maximization under knapsack constraint with linear query complexity J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-22 Canh V. Pham
In this work, we consider the Submodular Maximization under Knapsack (\(\textsf{SMK}\)) constraint problem over the ground set of size n. The problem recently attracted a lot of attention due to its applications in various domains of combinatorial optimization, artificial intelligence, and machine learning. We improve the approximation factor of the fastest deterministic algorithm from \(6+\epsilon
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Different due-window assignment scheduling with deterioration effects J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-13 Yurong Zhang, Xi Wang, Li-Han Zhang, Xue Jia, Ji-Bo Wang
This paper studies a due-window assignment scheduling problem with deterioration effects on a single-machine. Under different due-window assignment, i.e., the due-window of a job without any restriction, our goal is to make a decision on the optimal due-window and sequence of all jobs to minimize the weighted sum of earliness and tardiness, number of early and delayed, due-window starting time and
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An upper bound for neighbor-connectivity of graphs J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-13 Hongliang Ma, Baoyindureng Wu
The neighbor-connectivity of a graph G, denoted by \(\kappa _{NB}(G)\), is the least number of vertices such that removing their closed neighborhoods from G results in a graph that is empty, complete, or disconnected. In the paper, we show that for any graph G of order n, \(\kappa _{NB}(G)\le \lceil \sqrt{2n}\ \rceil -2\). We pose a conjecture that \(\kappa _{NB}(G)\le \lceil \sqrt{n}\ \rceil -1\)
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A novel arctic fox survival strategy inspired optimization algorithm J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-14 E. Subha, V. Jothi Prakash, S. Arul Antran Vijay
In the field of optimization algorithms, nature-inspired techniques have garnered attention for their adaptability and problem-solving prowess. This research introduces the Arctic Fox Algorithm (AFA), an innovative optimization technique inspired by the adaptive survival strategies of the Arctic fox, designed to excel in dynamic and complex optimization landscapes. Incorporating gradient flow dynamics
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Dynamic time window based full-view coverage maximization in CSNs J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-13 Jingfang Su, Zeqing Li, Hongwei Du, Shengxin Liu
In order to maximize full-view coverage of moving targets in Camera Sensor Networks (CSNs), a novel method known as “group set cover” is presented in this research. Choosing the best camera angles and placements to accomplish full-view coverage of the moving targets is one of the main focuses of the research in CSNs. Discretize the target into multiple views of [0, 2\(\pi \)], use a set of views of
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On injective chromatic index of sparse graphs with maximum degree 5 J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-07 Jian Lu, Zhen-Mu Hong, Zheng-Jiang Xia
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The sum of root-leaf distance interdiction problem with cardinality constraint by upgrading edges on trees J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-05 Xiao Li, Xiucui Guan, Qiao Zhang, Xinyi Yin, Panos M. Pardalos
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Non-submodular maximization with a decomposable objective function J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-05 Cheng Lu, Wenguo Yang
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Minimum $$ s-t $$ hypercut in (s, t)-planar hypergraphs J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-01 Abolfazl Hassanpour, Massoud Aman, Alireza Ebrahimi
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Maximizing diversity and persuasiveness of opinion articles in social networks J. Comb. Optim. (IF 0.9) Pub Date : 2024-11-01 Liman Du, Wenguo Yang, Suixiang Gao
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On greedy approximation algorithm for the minimum resolving dominating set problem J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-28 Hao Zhong
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Fashion game on graphs with more than two actions J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-28 Qi Wang, Wensong Lin
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Algorithms for the bin packing problem with scenarios J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-24 Yulle G. F. Borges, Vinícius L. de Lima, Flávio K. Miyazawa, Lehilton L. C. Pedrosa, Thiago A. de Queiroz, Rafael C. S. Schouery
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A MILP model for the connected multidimensional maximum bisection problem J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-22 Zoran Lj. Maksimović
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Optimizing hospital bed allocation for coordinated medical efficiency and quality improvement J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-21 Haiyue Yu, Ting Shen, Liwei Zhong
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The hamiltonian path graph is connected for simple s, t paths in rectangular grid graphs J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-19 Rahnuma Islam Nishat, Venkatesh Srinivasan, Sue Whitesides
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Efficient heuristics to compute minimal and stable feedback arc sets J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-15 Claudia Cavallaro, Vincenzo Cutello, Mario Pavone
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New approximations for monotone submodular maximization with knapsack constraint J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-13 Hongmin W. Du, Xiang Li, Guanghua Wang
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Explicit construction of mixed dominating sets in generalized Petersen graphs J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-14 Meysam Rajaati Bavil Olyaei, Mohsen Alambardar Meybodi, Mohammad Reza Hooshmandasl, Ali Shakiba
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Minimizing the maximum lateness for scheduling with release times and job rejection J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-11 Imed Kacem, Hans Kellerer
We study scheduling problems with release times and rejection costs with the objective function of minimizing the maximum lateness. Our main result is a PTAS for the single machine problem with an upper bound on the rejection costs. This result is extended to parallel, identical machines. The corresponding problem of minimizing the rejection costs with an upper bound on the lateness is also examined
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A common generalization of budget games and congestion games J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-11 Fuga Kiyosue, Kenjiro Takazawa
Budget games were introduced by Drees, Riechers, and Skopalik (2014) as a model of noncooperative games arising from resource allocation problems. Budget games have several similarities to congestion games, one of which is that the matroid structure of the strategy space is essential for the existence of a pure Nash equilibrium (PNE). Despite these similarities, however, the theoretical relation between
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Algorithmic study on liar’s vertex-edge domination problem J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-11 Debojyoti Bhattacharya, Subhabrata Paul
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W-prize-collecting scheduling problem on parallel machines J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-11 Bo Hou, Tianjiao Guo, Suogang Gao, Guanghua Wang, Weili Wu, Wen Liu
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Approximate weak efficiency of the set-valued optimization problem with variable ordering structures J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-12 Zhiang Zhou, Wenbin Wei, Fei Huang, Kequan Zhao
In locally convex spaces, we introduce the new notion of approximate weakly efficient solution of the set-valued optimization problem with variable ordering structures (in short, SVOPVOS) and compare it with other kinds of solutions. Under the assumption of near \(\mathcal {D}(\cdot )\)-subconvexlikeness, we establish linear scalarization theorems of (SVOPVOS) in the sense of approximate weak efficiency
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Approximation algorithm for prize-collecting vertex cover with fairness constraints J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-07 Mingchao Zhou, Zhao Zhang, Ding-Zhu Du
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Approximation algorithms for solving the trip-constrained vehicle routing cover problems J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-07 Jianping Li, Ping Yang, Junran Lichen, Pengxiang Pan
In this paper, we address the trip-constrained vehicle routing cover problem (the TcVRC problem). Specifically, given a metric complete graph \(G=(V,E;w)\) with a set D \((\subseteq V)\) of depots, a set J \((=V\backslash D)\) of customer locations, each customer having unsplittable demand 1, and k vehicles with capacity Q, it is asked to find a set \({\mathcal {C}}\) \(=\{C_i~|~i=1,2,\ldots ,k\}\)
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Construction of floorplans for plane graphs over polygonal boundaries J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-07 Rohit Lohani, Krishnendra Shekhawat
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Faster algorithms for evacuation problems in networks with a single sink of small degree and bounded capacitated edges J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-07 Yuya Higashikawa, Naoki Katoh, Junichi Teruyama, Yuki Tokuni
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Matroid-rooted packing of arborescences J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-07 Zoltán Szigeti
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The k-th Roman domination problem is polynomial on interval graphs J. Comb. Optim. (IF 0.9) Pub Date : 2024-10-05 Peng Li
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Efficient branch-and-bound algorithms for finding triangle-constrained 2-clubs J. Comb. Optim. (IF 0.9) Pub Date : 2024-09-21 Niels Grüttemeier, Philipp Heinrich Keßler, Christian Komusiewicz, Frank Sommer
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Minmax regret 1-sink location problems on dynamic flow path networks with parametric weights J. Comb. Optim. (IF 0.9) Pub Date : 2024-08-26 Tetsuya Fujie, Yuya Higashikawa, Naoki Katoh, Junichi Teruyama, Yuki Tokuni
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Efficient estimation of the modified Gromov–Hausdorff distance between unweighted graphs J. Comb. Optim. (IF 0.9) Pub Date : 2024-08-23 Vladyslav Oles, Nathan Lemons, Alexander Panchenko