Pub Date : 2026-03-14DOI: 10.1007/s10878-026-01412-9
Josep Freixas, Dani Samaniego
This paper considers resolute decision rules in which each voter may vote “yes", “abstain" or vote “no", and the outcome is “yes" or “no". The model we consider is more general than that of simple games since the input admits abstention or indecision, but it is more specialized since it assumes the properties of monotonicity and anonymity. Many subclasses of these resolute decision rules have been studied in the literature from an axiomatic point of view. The purpose of this work is to enumerate these subclasses as a function of the number of voters.
{"title":"On the enumeration of resolute majority rules","authors":"Josep Freixas, Dani Samaniego","doi":"10.1007/s10878-026-01412-9","DOIUrl":"https://doi.org/10.1007/s10878-026-01412-9","url":null,"abstract":"This paper considers resolute decision rules in which each voter may vote “yes\", “abstain\" or vote “no\", and the outcome is “yes\" or “no\". The model we consider is more general than that of simple games since the input admits abstention or indecision, but it is more specialized since it assumes the properties of monotonicity and anonymity. Many subclasses of these resolute decision rules have been studied in the literature from an axiomatic point of view. The purpose of this work is to enumerate these subclasses as a function of the number of voters.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"126 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147461815","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}
Pub Date : 2026-03-14DOI: 10.1007/s10878-026-01407-6
Luís Cunha, Mário Medina
Given a binary string <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> over the alphabet <jats:inline-formula> <jats:alternatives> <jats:tex-math>$${0, 1}$$</jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>{</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:math> </jats:alternatives> </jats:inline-formula> , a vector ( <jats:italic>a</jats:italic> , <jats:italic>b</jats:italic> ) is a Parikh vector if and only if a factor of <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> contains exactly <jats:italic>a</jats:italic> occurrences of 0 and <jats:italic>b</jats:italic> occurrences of 1. Answering whether a vector is a Parikh vector of <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> is known as the Binary Jumbled Indexing Problem ( <jats:sc>BJIP</jats:sc> ) or the Histogram Indexing Problem. Most solutions to this problem rely on an <jats:italic>O</jats:italic> ( <jats:italic>n</jats:italic> ) word-space index to answer queries in constant time, encoding the Parikh set of <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> , i.e., all its Parikh vectors. Cunha et al. ( <jats:italic>Combinatorial Pattern Matching</jats:italic> , 2017) introduced an algorithm ( <jats:italic>JBM2017</jats:italic> ), which computes the index table in <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$O(n+rho ^2)$$</jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>O</mml:mi> <mml:mo>(</mml:mo> <mml:mi>n</mml:mi> <mml:mo>+</mml:mo> <mml:msup> <mml:mi>ρ</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> </jats:alternatives> </jats:inline-formula> time, where <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$rho $$</jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ρ</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> is the number of runs of identical digits in <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> , leading to <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$O(n^2)$$</jats:tex-math> <mml:math xmlns:mm
{"title":"Binary jumbled indexing: suffix tree histogram","authors":"Luís Cunha, Mário Medina","doi":"10.1007/s10878-026-01407-6","DOIUrl":"https://doi.org/10.1007/s10878-026-01407-6","url":null,"abstract":"Given a binary string <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> over the alphabet <jats:inline-formula> <jats:alternatives> <jats:tex-math>$${0, 1}$$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mo>{</mml:mo> <mml:mn>0</mml:mn> <mml:mo>,</mml:mo> <mml:mn>1</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:math> </jats:alternatives> </jats:inline-formula> , a vector ( <jats:italic>a</jats:italic> , <jats:italic>b</jats:italic> ) is a Parikh vector if and only if a factor of <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> contains exactly <jats:italic>a</jats:italic> occurrences of 0 and <jats:italic>b</jats:italic> occurrences of 1. Answering whether a vector is a Parikh vector of <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> is known as the Binary Jumbled Indexing Problem ( <jats:sc>BJIP</jats:sc> ) or the Histogram Indexing Problem. Most solutions to this problem rely on an <jats:italic>O</jats:italic> ( <jats:italic>n</jats:italic> ) word-space index to answer queries in constant time, encoding the Parikh set of <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> , i.e., all its Parikh vectors. Cunha et al. ( <jats:italic>Combinatorial Pattern Matching</jats:italic> , 2017) introduced an algorithm ( <jats:italic>JBM2017</jats:italic> ), which computes the index table in <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$O(n+rho ^2)$$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mi>O</mml:mi> <mml:mo>(</mml:mo> <mml:mi>n</mml:mi> <mml:mo>+</mml:mo> <mml:msup> <mml:mi>ρ</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> </jats:alternatives> </jats:inline-formula> time, where <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$rho $$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mi>ρ</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> is the number of runs of identical digits in <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$omega $$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mi>ω</mml:mi> </mml:math> </jats:alternatives> </jats:inline-formula> , leading to <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$O(n^2)$$</jats:tex-math> <mml:math xmlns:mm","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"130 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147462160","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}
Pub Date : 2026-03-07DOI: 10.1007/s10878-026-01410-x
Louis Stubbe, Jens Goemaere, Jan Goedgebeur
{"title":"Online dispatching and routing for automated guided vehicles in pickup and delivery systems on loop-based graphs","authors":"Louis Stubbe, Jens Goemaere, Jan Goedgebeur","doi":"10.1007/s10878-026-01410-x","DOIUrl":"https://doi.org/10.1007/s10878-026-01410-x","url":null,"abstract":"","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"3 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147373856","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}
Pub Date : 2026-03-07DOI: 10.1007/s10878-026-01405-8
Gabriel Siqueira, Klairton Lima Brito, Alexsandro Oliveira Alexandrino, Andre Rodrigues Oliveira, Ulisses Dias, Zanoni Dias
In genome rearrangement, graph-based representations are widely used to analyze and solve rearrangement problems. In particular, when each gene occurs at most once, the breakpoint graph is a useful tool. A maximum cycle decomposition of this graph yields immediate lower bounds for several genome rearrangement distances. This paper introduces a generalization of the Maximum Alternating Cycle Decomposition problem ( MAX-ACD ), called the Maximum Alternating Clean Balanced Cycle Decomposition problem ( MAX-ACBCD ). The MAX-ACD problem is closely related to some rearrangement problems, where the orientation of the genes is unknown, and all genes are common to both genomes. The MAX-ACBCD problem has applications to related rearrangement problems, which allow genes present in only one of the genomes and consider both gene order and intergenic-region information. We present a constant-factor approximation and a heuristic for the MAX-ACBCD problem, and we performed tests with the heuristic applied to artificially generated genomes. Considering intergenic regions and a scenario where the orientation of the genes is known, we design an improved algorithm for the Sorting by Reversals and Intergenic Indels problem that guarantees an approximation factor of $$frac{3}{2}$$32 . For the scenario where the orientation of the genes is unknown, and using the MAX-ACBCD problem, we develop approximation algorithms for the Sorting by Reversals, the Sorting by Reversals and Intergenic Indels, the Reversal, Transposition and Indel Distance, the Sorting by DCJ, and the Sorting by DCJ and Intergenic Indels problems with approximation factors of 2 k , $$frac{3k}{2}$$3k2 , 4 k , 2 k , and k , respectively, where $$k=frac{31}{21}+epsilon $$k=3121+ϵ .
在基因组重排中，基于图的表示被广泛用于分析和解决重排问题。特别是，当每个基因最多出现一次时，断点图是一个有用的工具。对这个图进行最大循环分解，可以得到几个基因组重排距离的直接下界。本文介绍了最大交替循环分解问题（MAX-ACD）的一种推广，称为最大交替清洁平衡循环分解问题（MAX-ACBCD）。MAX-ACD问题与一些重排问题密切相关，在这些重排问题中，基因的取向是未知的，所有的基因在两个基因组中都是共同的。MAX-ACBCD问题适用于相关的重排问题，该问题允许基因仅存在于一个基因组中，并考虑基因顺序和基因间区域信息。对于MAX-ACBCD问题，我们提出了常因子近似和启发式方法，并将启发式方法应用于人工生成的基因组进行了测试。考虑到基因间区域和基因取向已知的情况，我们设计了一种改进的逆排序和基因间索引问题算法，该算法保证近似因子为$$frac{3}{2}$$ 32。对于基因方向未知的情况，使用MAX-ACBCD问题，我们开发了近似算法，分别适用于逆排序、逆排序和基因间索引、反转、转置和Indel距离、DCJ排序、DCJ排序和基因间索引问题，近似因子分别为2 k、$$frac{3k}{2}$$ 3 k 2、4 k、2 k和k，其中$$k=frac{31}{21}+epsilon $$ k = 31 21 + ε。
{"title":"Maximum alternating clean balanced cycle decomposition and applications in rearrangement distance problems","authors":"Gabriel Siqueira, Klairton Lima Brito, Alexsandro Oliveira Alexandrino, Andre Rodrigues Oliveira, Ulisses Dias, Zanoni Dias","doi":"10.1007/s10878-026-01405-8","DOIUrl":"https://doi.org/10.1007/s10878-026-01405-8","url":null,"abstract":"In genome rearrangement, graph-based representations are widely used to analyze and solve rearrangement problems. In particular, when each gene occurs at most once, the breakpoint graph is a useful tool. A maximum cycle decomposition of this graph yields immediate lower bounds for several genome rearrangement distances. This paper introduces a generalization of the Maximum Alternating Cycle Decomposition problem ( <jats:sc>MAX-ACD</jats:sc> ), called the Maximum Alternating Clean Balanced Cycle Decomposition problem ( <jats:sc>MAX-ACBCD</jats:sc> ). The <jats:sc>MAX-ACD</jats:sc> problem is closely related to some rearrangement problems, where the orientation of the genes is unknown, and all genes are common to both genomes. The <jats:sc>MAX-ACBCD</jats:sc> problem has applications to related rearrangement problems, which allow genes present in only one of the genomes and consider both gene order and intergenic-region information. We present a constant-factor approximation and a heuristic for the <jats:sc>MAX-ACBCD</jats:sc> problem, and we performed tests with the heuristic applied to artificially generated genomes. Considering intergenic regions and a scenario where the orientation of the genes is known, we design an improved algorithm for the Sorting by Reversals and Intergenic Indels problem that guarantees an approximation factor of <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$frac{3}{2}$$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mfrac> <mml:mn>3</mml:mn> <mml:mn>2</mml:mn> </mml:mfrac> </mml:math> </jats:alternatives> </jats:inline-formula> . For the scenario where the orientation of the genes is unknown, and using the <jats:sc>MAX-ACBCD</jats:sc> problem, we develop approximation algorithms for the Sorting by Reversals, the Sorting by Reversals and Intergenic Indels, the Reversal, Transposition and Indel Distance, the Sorting by DCJ, and the Sorting by DCJ and Intergenic Indels problems with approximation factors of 2 <jats:italic>k</jats:italic> , <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$frac{3k}{2}$$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mfrac> <mml:mrow> <mml:mn>3</mml:mn> <mml:mi>k</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:mfrac> </mml:math> </jats:alternatives> </jats:inline-formula> , 4 <jats:italic>k</jats:italic> , 2 <jats:italic>k</jats:italic> , and <jats:italic>k</jats:italic> , respectively, where <jats:inline-formula> <jats:alternatives> <jats:tex-math>$$k=frac{31}{21}+epsilon $$</jats:tex-math> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mi>k</mml:mi> <mml:mo>=</mml:mo> <mml:mfrac> <mml:mn>31</mml:mn> <mml:mn>21</mml:mn> </mml:mfrac> <mml:mo>+</mml:mo> <mml:mi>ϵ</mml:mi> </mml:mrow> </mml:math> </jats:alternatives> </jats:inline-formula> .","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"30 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147373855","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}
Pub Date : 2026-03-07DOI: 10.1007/s10878-026-01397-5
Ying Chen, Yongxi Cheng, Jun Wu, Guiqing Zhang
{"title":"Optimal due date assignment in a single machine group technology scheduling environment with learning effect","authors":"Ying Chen, Yongxi Cheng, Jun Wu, Guiqing Zhang","doi":"10.1007/s10878-026-01397-5","DOIUrl":"https://doi.org/10.1007/s10878-026-01397-5","url":null,"abstract":"","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"36 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147373857","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}
Pub Date : 2026-03-07DOI: 10.1007/s10878-026-01406-7
Niranka Banerjee, Duc A. Hoang
{"title":"The complexity of distance-r dominating set reconfiguration","authors":"Niranka Banerjee, Duc A. Hoang","doi":"10.1007/s10878-026-01406-7","DOIUrl":"https://doi.org/10.1007/s10878-026-01406-7","url":null,"abstract":"","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"17 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147373858","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}
Pub Date : 2026-03-07DOI: 10.1007/s10878-026-01408-5
Wajih Abdallah
{"title":"Federated edge intelligence for secure and adaptive routing in IoT: a GRU–RL based framework","authors":"Wajih Abdallah","doi":"10.1007/s10878-026-01408-5","DOIUrl":"https://doi.org/10.1007/s10878-026-01408-5","url":null,"abstract":"","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"241 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147373854","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}
Pub Date : 2026-03-07DOI: 10.1007/s10878-026-01402-x
V. Sowmya, A. Rajeswari
{"title":"A multimodal meta-learning-augmented EmoTriSense for emotion recognition","authors":"V. Sowmya, A. Rajeswari","doi":"10.1007/s10878-026-01402-x","DOIUrl":"https://doi.org/10.1007/s10878-026-01402-x","url":null,"abstract":"","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"12 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147373860","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}
Pub Date : 2026-03-03DOI: 10.1007/s10878-026-01413-8
Zhaofang Mao, Yuqiong Jiang, Yufeng Liao
With the rapid advancement of health information technology and growing demand for efficient data sharing, Health Information Exchange (HIE) systems have gained increasing attention. However, research on HIE revenue schemes for asymmetric competitive healthcare providers (HPs) remains limited. This study develops a game-theoretic model to analyze the Health Information Exchange (HIE)’s optimal revenue-scheme selection under asymmetric competition between healthcare providers (HPs). Four combinations of subscription and fee-for-service (FFS) schemes are examined to derive equilibrium pricing, service quality, and welfare outcomes. To verify robustness, we conduct parameter sensitivity and Monte Carlo-based probabilistic analyses, showing that the welfare-optimal configuration (subscription for high-level HPs and FFS for low-level HPs) remains stable under the parameter uncertainty. Furthermore, the model is generalized to an N-HPs market, where the HIE’s revenue-scheme choice is formulated as a 0–1 combinatorial optimization problem. We prove a threshold structure and design a Sorting-and-Threshold Search Algorithm (STSA) that efficiently identifies stable welfare-maximizing assignments. Empirical case studies of U.S. HIEs validate the model and highlight adoption challenges and transitional incentives that promote sustainable implementation.
{"title":"Competition between healthcare providers under subscription and fee-for-service: an equilibrium analysis of health information exchange system’s choice","authors":"Zhaofang Mao, Yuqiong Jiang, Yufeng Liao","doi":"10.1007/s10878-026-01413-8","DOIUrl":"https://doi.org/10.1007/s10878-026-01413-8","url":null,"abstract":"With the rapid advancement of health information technology and growing demand for efficient data sharing, Health Information Exchange (HIE) systems have gained increasing attention. However, research on HIE revenue schemes for asymmetric competitive healthcare providers (HPs) remains limited. This study develops a game-theoretic model to analyze the Health Information Exchange (HIE)’s optimal revenue-scheme selection under asymmetric competition between healthcare providers (HPs). Four combinations of subscription and fee-for-service (FFS) schemes are examined to derive equilibrium pricing, service quality, and welfare outcomes. To verify robustness, we conduct parameter sensitivity and Monte Carlo-based probabilistic analyses, showing that the welfare-optimal configuration (subscription for high-level HPs and FFS for low-level HPs) remains stable under the parameter uncertainty. Furthermore, the model is generalized to an N-HPs market, where the HIE’s revenue-scheme choice is formulated as a 0–1 combinatorial optimization problem. We prove a threshold structure and design a Sorting-and-Threshold Search Algorithm (STSA) that efficiently identifies stable welfare-maximizing assignments. Empirical case studies of U.S. HIEs validate the model and highlight adoption challenges and transitional incentives that promote sustainable implementation.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"32 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147507829","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}
Pub Date : 2026-03-03DOI: 10.1007/s10878-026-01409-4
Dikshit Chauhan, Deepika Khurana, Anupam Yadav
Feature selection is a challenging combinatorial optimization problem that seeks to identify informative feature subsets from high-dimensional data while balancing classification accuracy and model interpretability. Traditional metaheuristic algorithms often experience premature convergence due to insufficient control over population diversity and exploration dynamics, especially in the case of high-dimensional combinatorial optimization problems. To overcome this limitation, this paper proposes a chaotic Artificial Electric Field Algorithm (cAEFA), in which chaotic strategies are systematically embedded into Coulomb’s constant, a core parameter governing agent interactions in AEFA. Unlike random perturbations, chaotic maps introduce deterministic yet ergodic dynamics that generate controlled diversity and enable adaptive regulation of exploration and exploitation across different search stages. Different chaotic strategies, which differ in their nonlinear behaviours and sensitivity to initial conditions, are used, which allows the algorithm to exhibit varied search trajectories and enhanced robustness. A normalization mechanism is further included to stabilize these chaotic influences to ensure smooth convergence. Extensive experimental results on forty-two benchmark problems from the IEEE CEC test suites and real-world feature selection problems demonstrate that cAEFA achieves superior solution quality, faster convergence, and improved generalization compared with state-of-the-art methods. These findings highlight the effectiveness of chaos-driven parameter modulation as a principled mechanism for enhancing metaheuristic search performance. The MATLAB code of cAEFA can be found at https://github.com/ChauhanDikshit.
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