Journal of Combinatorial Optimization最新文献_第5页

Planar graphs are acyclically edge $$(Delta + 5)$$ -colorable 平面图具有非循环边$$(Delta + 5)$$ -可着色性

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-27 DOI: 10.1007/s10878-024-01165-3

Qiaojun Shu, Guohui Lin

引用次数: 0

Hybrid optimized deep recurrent neural network for atmospheric and oceanic parameters prediction by feature fusion and data augmentation model 通过特征融合和数据增强模型预测大气和海洋参数的混合优化深度递归神经网络

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-27 DOI: 10.1007/s10878-024-01159-1

Sundeep Raj, Sandesh Tripathi, K. C. Tripathi, Rajendra Kumar Bharti

{"title":"Hybrid optimized deep recurrent neural network for atmospheric and oceanic parameters prediction by feature fusion and data augmentation model","authors":"Sundeep Raj, Sandesh Tripathi, K. C. Tripathi, Rajendra Kumar Bharti","doi":"10.1007/s10878-024-01159-1","DOIUrl":"https://doi.org/10.1007/s10878-024-01159-1","url":null,"abstract":"In recent years climate prediction has obtained more attention to mitigate the impact of natural disasters caused by climatic variability. Efficient and effective climate prediction helps palliate negative consequences and allows favourable conditions for managing the resources optimally through proper planning. Due to the environmental, geopolitical and economic consequences, forecasting of atmospheric and oceanic parameters still results in a challenging task. An efficient prediction technique named Sea Lion Autoregressive Deer Hunting Optimization-based Deep Recurrent Neural Network (SLArDHO-based Deep RNN) is developed in this research to predict the oceanic and atmospheric parameters. The extraction of technical indicators makes the devised method create optimal and accurate prediction outcomes by employing the deep learning framework. The classifier uses more training samples and this can be generated by augmenting the data samples using the oversampling method. The atmospheric and the oceanic parameters are considered for the prediction strategy using the Deep RNN classifier. Here, the weights of the Deep RNN classifier are optimally tuned by the SLArDHO algorithm to find the best value based on the fitness function. The devised method obtains minimum mean squared error (MSE), root mean square error (RMSE), mean absolute error (MAE) of 0.020, 0.142, and 0.029 for the All India Rainfall Index (AIRI) dataset.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140807367","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

Constrained heterogeneous two-facility location games with sum-variant 具有和变数的受约束异质双设施位置博弈

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-27 DOI: 10.1007/s10878-024-01163-5

Qi Zhao, Wenjing Liu, Qingqin Nong, Qizhi Fang

{"title":"Constrained heterogeneous two-facility location games with sum-variant","authors":"Qi Zhao, Wenjing Liu, Qingqin Nong, Qizhi Fang","doi":"10.1007/s10878-024-01163-5","DOIUrl":"https://doi.org/10.1007/s10878-024-01163-5","url":null,"abstract":"We study deterministic mechanism design for constrained heterogeneous two-facility location games. The constraint here means that the feasible locations of facilities are specified and the number of facilities that can be built at each feasible location is limited. Given that a set of agents can strategically report their locations on the real line, the authority wants to design strategyproof mechanisms (i.e., mechanisms that can incentivize agents to report truthful private information) to construct two heterogeneous facilities under constraint, while optimizing the corresponding social objectives. Assuming that each agent’s individual objective depends on the sum of her distance to facilities, we consider locating desirable and obnoxious facilities respectively. For the former, we give a deterministic group strategyproof mechanism, which guarantees 3-approximation under the objectives of minimizing the sum cost and the maximum cost. We show that no deterministic strategyproof mechanism can have an approximation ratio of less than 2 under the sum/maximum cost objective. For the latter, we give a deterministic group strategyproof mechanism with 2-approximation under the objectives of maximizing the sum utility and the minimum utility. We show that no deterministic strategyproof mechanism can have an approximation ratio of less than 3/2 under the sum utility objective and 2 under the minimum utility objective, respectively.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140807380","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

Approximation algorithm for the minimum partial connected Roman dominating set problem 最小部分相连罗马支配集问题的近似计算算法

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-26 DOI: 10.1007/s10878-024-01124-y

Yaoyao Zhang, Zhao Zhang, Ding-Zhu Du

引用次数: 0

Spread of influence with incentives in edge-weighted graphs with emphasis on some families of graphs 边缘加权图中有激励机制的影响力扩散，重点是一些图族

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-25 DOI: 10.1007/s10878-024-01164-4

Siavash Askari, Manouchehr Zaker

{"title":"Spread of influence with incentives in edge-weighted graphs with emphasis on some families of graphs","authors":"Siavash Askari, Manouchehr Zaker","doi":"10.1007/s10878-024-01164-4","DOIUrl":"https://doi.org/10.1007/s10878-024-01164-4","url":null,"abstract":"Let (G=(V, E)) be a graph that represents an underlying network. Let (tau ) (resp. ({textbf{p}})) be an assignment of non-negative integers as thresholds (resp. incentives) to the vertices of G. The discrete time activation process with incentives corresponding to ((G, tau , {textbf{p}})) is the following. First, all vertices u with ({textbf{p}}(u)ge tau (u)) are activated. Then at each time t, every vertex u gets activated if the number of previously activated neighbors of u plus ({textbf{p}}(u)) is at least (tau (v)). The optimal target vector problem (OTV) is to find the minimum total incentives ({sum }_{vin V} {textbf{p}}(v)) that activates the whole network. We extend this model of activation with incentives, for graphs with weighted edges such that the spread of activation in the network depends on the weight of influence between any two participants. The new version is more realistic for the real world networks. We first prove that the new problem OTVW, is (texttt {NP})-complete even for the complete graphs. Two lower bounds for the minimum total incentives are presented. Next, we prove that OTVW has polynomial time solutions for (weighted) path and cycle graphs. Finally, we extend the discussed model and OTV, for bi-directed graphs with weighted edges and prove that to obtain the optimal target vector in weighted bi-directed paths and cycles has polynomial time solutions.\u0000","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140642742","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

Approximation algorithms for maximum weighted target cover problem with distance limitations 有距离限制的最大加权目标覆盖问题的近似算法

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-22 DOI: 10.1007/s10878-024-01166-2

Jianhong Jin, Yingli Ran, Zhao Zhang

{"title":"Approximation algorithms for maximum weighted target cover problem with distance limitations","authors":"Jianhong Jin, Yingli Ran, Zhao Zhang","doi":"10.1007/s10878-024-01166-2","DOIUrl":"https://doi.org/10.1007/s10878-024-01166-2","url":null,"abstract":"In this paper, we study approximation algorithms for the problem of maximum weighted target cover with distance limitations (MaxWTCDL). Given n targets (T=left{ t_{1},t_{2},ldots ,t_{n}right} ) on the plane and m mobile sensors (S=left{ s_{1},s_{2},ldots ,s_{m}right} ) randomly deployed on the plane, each target (t_i) has a weight (w_{i}) and the sensing radius of the mobile sensors is (r_{s}), suppose there is a movement distance constraint b for each sensor and a total movement distance constraint B, where (B>b), the goal of MaxWTCDL is to move the mobile sensors within the distance constraints b and B to maximize the weight of covered targets. We present two polynomial time approximation algorithms. One is greedy-based, achieving approximation ratio (frac{1}{2v}) in time (O(mn^2)), where . The other is LP-based, achieving approximation ratio (frac{1}{v}(1-e^{-1})) in time (T_{LP}), where (T_{LP}) is the time needed to solve the linear program.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140637638","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

Cooperation models in automotive supply chain under low-carbon emission reduction policies 低碳减排政策下汽车供应链的合作模式

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-21 DOI: 10.1007/s10878-024-01160-8

Yukun Cheng, Zhanghao Yao, Tingting Meng

{"title":"Cooperation models in automotive supply chain under low-carbon emission reduction policies","authors":"Yukun Cheng, Zhanghao Yao, Tingting Meng","doi":"10.1007/s10878-024-01160-8","DOIUrl":"https://doi.org/10.1007/s10878-024-01160-8","url":null,"abstract":"For the issue of carbon emission mitigation within the automotive supply chain, the cooperation between the vehicle manufacturers and the retailers has been proved to be an efficient measure to enhance emission reduction endeavors. This paper aims to evaluate the effectiveness of the cooperations between a vehicle manufacturer and multiple retailers based on the differential game method. By utilizing the Hamilton–Jacobi–Bellman equation, the equilibrium strategies of the participants under two different cooperation models, i.e., the decentralized model and the Stackelberg leader–follower cooperation model, are analyzed. To be specific, in the decentralized model, each participant independently decides its strategies, whereas the manufacturer cooperates with retailers by offering subsidies in the Stackelberg leader–follower model. Unlike previous studies that solely focused on participants’ decision-making in carbon emission reduction efforts, this paper also examines the retail pricing decisions of the retailers. Additionally, carbon trading is introduced to enhance the realism of our model. Through the theoretical analysis and the numerical experiments on the carbon emission reduction efforts of manufacturers and retailers, as well as the low-carbon reputation of vehicles and the overall system profit under both models, we conclude that the cooperative Stackelberg model outperforms the decentralized model in providing benefits to both parties. Furthermore, such a cooperative approach can foster the long-term development of the automotive supply chain, ultimately contributing to a more sustainable low-carbon future.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140622736","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

Differentially private submodular maximization with a cardinality constraint over the integer lattice 在整数网格上具有卡方约束的微分私有亚模块最大化计算

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-19 DOI: 10.1007/s10878-024-01158-2

Jiaming Hu, Dachuan Xu, Donglei Du, Cuixia Miao

{"title":"Differentially private submodular maximization with a cardinality constraint over the integer lattice","authors":"Jiaming Hu, Dachuan Xu, Donglei Du, Cuixia Miao","doi":"10.1007/s10878-024-01158-2","DOIUrl":"https://doi.org/10.1007/s10878-024-01158-2","url":null,"abstract":"The exploration of submodular optimization problems on the integer lattice offers a more precise approach to handling the dynamic interactions among repetitive elements in practical applications. In today’s data-driven world, the importance of efficient and reliable privacy-preserving algorithms has become paramount for safeguarding sensitive information. In this paper, we delve into the DR-submodular and lattice submodular maximization problems subject to cardinality constraints on the integer lattice, respectively. For DR-submodular functions, we devise a differential privacy algorithm that attains a ((1-1/e-rho ))-approximation guarantee with additive error (O(rsigma ln |N|/epsilon )) for any (rho >0), where N is the number of groundset, (epsilon ) is the privacy budget, r is the cardinality constraint, and (sigma ) is the sensitivity of a function. Our algorithm preserves (O(epsilon r^{2}))-differential privacy. Meanwhile, for lattice submodular functions, we present a differential privacy algorithm that achieves a ((1-1/e-O(rho )))-approximation guarantee with additive error (O(rsigma ln |N|/epsilon )). We evaluate their effectiveness using instances of the combinatorial public projects problem and the budget allocation problem within the bipartite influence model.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140621491","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

Maximum size of a triangle-free graph with bounded maximum degree and matching number 最大度数和匹配数有界的无三角形图的最大尺寸

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-16 DOI: 10.1007/s10878-024-01123-z

Milad Ahanjideh, Tınaz Ekim, Mehmet Akif Yıldız

{"title":"Maximum size of a triangle-free graph with bounded maximum degree and matching number","authors":"Milad Ahanjideh, Tınaz Ekim, Mehmet Akif Yıldız","doi":"10.1007/s10878-024-01123-z","DOIUrl":"https://doi.org/10.1007/s10878-024-01123-z","url":null,"abstract":"Determining the maximum number of edges under degree and matching number constraints have been solved for general graphs in Chvátal and Hanson (J Combin Theory Ser B 20:128–138, 1976) and Balachandran and Khare (Discrete Math 309:4176–4180, 2009). It follows from the structure of those extremal graphs that deciding whether this maximum number decreases or not when restricted to claw-free graphs, to (C_4)-free graphs or to triangle-free graphs are separately interesting research questions. The first two cases being already settled in Dibek et al. (Discrete Math 340:927–934, 2017) and Blair et al. (Latin American symposium on theoretical informatics, 2020), in this paper we focus on triangle-free graphs. We show that unlike most cases for claw-free graphs and (C_4)-free graphs, forbidding triangles from extremal graphs causes a strict decrease in the number of edges and adds to the hardness of the problem. We provide a formula giving the maximum number of edges in a triangle-free graph with degree at most d and matching number at most m for all cases where (dge m), and for the cases where (d<m) with either (dle 6) or (Z(d)le m < 2d) where Z(d) is a function of d which is roughly 5d/4. We also provide an integer programming formulation for the remaining cases and as a result of further discussion on this formulation, we conjecture that our formula giving the size of triangle-free extremal graphs is also valid for these open cases.\u0000","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140556768","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

Branch-and-cut-and-price algorithm for the constrained-routing and spectrum assignment problem 受限路由和频谱分配问题的分支-切割-价格算法

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2024-04-14 DOI: 10.1007/s10878-024-01125-x

Ibrahima Diarrassouba, Youssouf Hadhbi, A. Ridha Mahjoub

引用次数: 0