Journal of Combinatorial Optimization最新文献

Enhanced deterministic approximation algorithm for non-monotone submodular maximization under knapsack constraint with linear query complexity 具有线性查询复杂度的knapsack约束下非单调亚模块最大化的增强确定性近似算法

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-22 DOI: 10.1007/s10878-024-01232-9

Canh V. Pham

引用次数: 0

A novel arctic fox survival strategy inspired optimization algorithm 受北极狐生存策略启发的新型优化算法

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-14 DOI: 10.1007/s10878-024-01233-8

E. Subha, V. Jothi Prakash, S. Arul Antran Vijay

{"title":"A novel arctic fox survival strategy inspired optimization algorithm","authors":"E. Subha, V. Jothi Prakash, S. Arul Antran Vijay","doi":"10.1007/s10878-024-01233-8","DOIUrl":"https://doi.org/10.1007/s10878-024-01233-8","url":null,"abstract":"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, stochastic differential equations, and probability distributions, AFA is equipped to adjust its search strategies dynamically, enhancing both exploration and exploitation capabilities. Through rigorous evaluation on a set of 25 benchmark functions, AFA consistently outperformed established algorithms particularly in scenarios involving high-dimensional and multi-modal problems, demonstrating faster convergence and improved solution quality. Application of AFA to real-world problems, including wind farm layout optimization and financial portfolio optimization, highlighted its ability to increase energy outputs by up to 15% and improve portfolio Sharpe ratios by 20% compared to conventional methods. These results showcase AFA’s potential as a robust tool for complex optimization tasks, paving the way for future research focused on refining its adaptive mechanisms and exploring broader applications.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"8 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142673162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic time window based full-view coverage maximization in CSNs CSN 中基于动态时间窗口的全视角覆盖最大化

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-13 DOI: 10.1007/s10878-024-01227-6

Jingfang Su, Zeqing Li, Hongwei Du, Shengxin Liu

引用次数: 0

An upper bound for neighbor-connectivity of graphs 图的邻接连通性上限

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-13 DOI: 10.1007/s10878-024-01235-6

Hongliang Ma, Baoyindureng Wu

引用次数: 0

Different due-window assignment scheduling with deterioration effects 具有恶化效应的不同到期窗口分配调度

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-13 DOI: 10.1007/s10878-024-01223-w

Yurong Zhang, Xi Wang, Li-Han Zhang, Xue Jia, Ji-Bo Wang

引用次数: 0

On injective chromatic index of sparse graphs with maximum degree 5 论最大阶数为 5 的稀疏图的注入色度指数

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-07 DOI: 10.1007/s10878-024-01234-7

Jian Lu, Zhen-Mu Hong, Zheng-Jiang Xia

引用次数: 0

Non-submodular maximization with a decomposable objective function 目标函数可分解的非次模态最大化

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-05 DOI: 10.1007/s10878-024-01224-9

Cheng Lu, Wenguo Yang

{"title":"Non-submodular maximization with a decomposable objective function","authors":"Cheng Lu, Wenguo Yang","doi":"10.1007/s10878-024-01224-9","DOIUrl":"https://doi.org/10.1007/s10878-024-01224-9","url":null,"abstract":"We study the non-submodular maximization problem, whose objective function can be expressed as the Difference between two Set (DS) functions or the Ratio between two Set (RS) functions. For the cardinality-constrained and unconstrained DS maximization problems, we present several deterministic algorithms and our analysis shows that the algorithms can provide provable approximation guarantees. As an application, we manage to derive an improved approximation bound for the DS minimization problem under certain conditions compared with existing results. As for the RS maximization problem, we show that there exists a polynomial-time reduction from the approximation of RS maximization to the approximation of DS maximization. Based on this reduction, we derive the first approximation bound for the cardinality-constrained RS maximization problem. We also devise algorithms for the unconstrained problem and analyze their approximation guarantees. By applying our results to the problem of optimizing the ratio between two supermodular functions, we give an answer to the question posed by Bai et al. (in Proceedings of The 33rd international conference on machine learning (ICML), 2016). Moreover, we give an example to illustrate that whether the set function is normalized has an effect on the approximability of the RS optimization problem.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"242 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142580292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The sum of root-leaf distance interdiction problem with cardinality constraint by upgrading edges on trees 通过提升树上的边来解决有卡片数量限制的根叶距离阻断问题的总和

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-05 DOI: 10.1007/s10878-024-01230-x

Xiao Li, Xiucui Guan, Qiao Zhang, Xinyi Yin, Panos M. Pardalos

{"title":"The sum of root-leaf distance interdiction problem with cardinality constraint by upgrading edges on trees","authors":"Xiao Li, Xiucui Guan, Qiao Zhang, Xinyi Yin, Panos M. Pardalos","doi":"10.1007/s10878-024-01230-x","DOIUrl":"https://doi.org/10.1007/s10878-024-01230-x","url":null,"abstract":"A network for the transportation of supplies can be described as a rooted tree with a weight of a degree of congestion for each edge. We take the sum of root-leaf distance (SRD) on a rooted tree as the whole degree of congestion of the tree. Hence, we consider the SRD interdiction problem on trees with cardinality constraint by upgrading edges, denoted by (SDIPTC). It aims to maximize the SRD by upgrading the weights of N critical edges such that the total upgrade cost under some measurement is upper-bounded by a given value. The relevant minimum cost problem (MCSDIPTC) aims to minimize the total upgrade cost on the premise that the SRD is lower-bounded by a given value. We develop two different norms including weighted (l_infty ) norm and weighted bottleneck Hamming distance to measure the upgrade cost. We propose two binary search algorithms within O((nlog n)) time for the problems (SDIPTC) under the two norms, respectively. For problems (MCSDIPTC), we propose two binary search algorithms within O((N n^2)) and O((n log n)) under weighted (l_infty ) norm and weighted bottleneck Hamming distance, respectively. These problems are solved through their subproblems (SDIPT) and (MCSDIPT), in which we ignore the cardinality constraint on the number of upgraded edges. Finally, we design numerical experiments to show the effectiveness of these algorithms.\u0000","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"17 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142580291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Minimum $$ s-t $$ hypercut in (s, t)-planar hypergraphs (s, t)平面超图中的最小 $$ s-t$ 超切线

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-01 DOI: 10.1007/s10878-024-01231-w

Abolfazl Hassanpour, Massoud Aman, Alireza Ebrahimi

引用次数: 0

Maximizing diversity and persuasiveness of opinion articles in social networks 最大限度地提高社交网络中观点文章的多样性和说服力

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-11-01 DOI: 10.1007/s10878-024-01226-7

Liman Du, Wenguo Yang, Suixiang Gao

{"title":"Maximizing diversity and persuasiveness of opinion articles in social networks","authors":"Liman Du, Wenguo Yang, Suixiang Gao","doi":"10.1007/s10878-024-01226-7","DOIUrl":"https://doi.org/10.1007/s10878-024-01226-7","url":null,"abstract":"Social-media platforms have created new ways for individuals to keep in touch with others, share their opinions and join the discussion on different issues. Traditionally studied by social science, opinion dynamic has attracted the attention from scientists in other fields. The formation and evolution of opinions is a complex process affected by the interplay of different elements that incorporate peer interaction in social networks and the diversity of information to which each individual is exposed. In addition, supplementary information can have an important role in driving the opinion formation and evolution. And due to the character of online social platforms, people can easily end an existing follower-followee relationship or stop interacting with a friend at any time. Taking a step in this direction, we propose the OG–IC model which considers the dynamic of both opinion and relationship in this paper. It not only considers the direct influence of friends but also highlights the indirect effect of group when individuals are exposed to new opinions. And it allows nodes which represent users of social networks to slightly adjust their own opinion and sometimes redefine friendships. A novel problem in social network whose purpose is simultaneously maximizing both the diversity of supplementary information that individuals access to and the influence of supplementary information on individual’s existing opinion is formulated. This problem is proved to be NP-hard and its objective function is neither submodular nor supermodular. However, an algorithm with approximate ratio guarantee is designed based on the sandwich framework. And the effectiveness of our algorithm is experimentally demonstrated on both synthetic and real-world data sets.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"79 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142563302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0