Journal of Combinatorial Optimization最新文献_第3页

Single-machine scheduling with the learning effect of processing time and the deterioration effect of delivery time for prefabricated components

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-03-13 DOI: 10.1007/s10878-025-01271-w

Na Li, Ran Ma, Yuzhong Zhang

{"title":"Single-machine scheduling with the learning effect of processing time and the deterioration effect of delivery time for prefabricated components","authors":"Na Li, Ran Ma, Yuzhong Zhang","doi":"10.1007/s10878-025-01271-w","DOIUrl":"https://doi.org/10.1007/s10878-025-01271-w","url":null,"abstract":"In the production scheduling of prefabricated components, a scheduling model considering the learning effect of processing time and the deterioration effect of delivery time in this paper is provided. More precisely, it asks for an assignment of a series of independent prefabricated jobs that arrived over time to a single machine for processing, and once the execution of a job is finished, it will be transported to the destination. The information of each prefabricated job including its basic processing time (b_{j}), release time (r_j), and deterioration rate (e_j) of delivery time is unknown in advance and is revealed upon the arrival of this job. Moreover, the actual processing time of prefabricated job (J_j) with learning effect is (p_{j}=b_{j}(a-b t)), where a and b are non-negative parameters and t denotes the starting time of prefabricated job (J_j), respectively. And the delivery time of prefabricated job (J_j) is (q_{j}=e_{j}C_{j}). The goal of scheduling is to minimize the maximum time by which all jobs have been delivered. For the problem, we first analyze offline optimal scheduling and then propose an online algorithm with a competitive ratio of (2-bb_{min }). Furthermore, the effectiveness of the online algorithm is demonstrated by numerical experiments and managerial insights are derived.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"56 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143618466","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

Some results on the total (zero) forcing number of a graph

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-03-10 DOI: 10.1007/s10878-025-01268-5

Jianxi Li, Dongxin Tu, Wai Chee Shiu

引用次数: 0

Enhancing decision-making in cloud service provider selection using probabilistic p, q-rung orthopair fuzzy model

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-03-05 DOI: 10.1007/s10878-025-01269-4

Pairote Yiarayong

{"title":"Enhancing decision-making in cloud service provider selection using probabilistic p, q-rung orthopair fuzzy model","authors":"Pairote Yiarayong","doi":"10.1007/s10878-025-01269-4","DOIUrl":"https://doi.org/10.1007/s10878-025-01269-4","url":null,"abstract":"Desktop cloud technology has revolutionized modern computing by enabling remote desktop functionality through cloud computing and virtualization. However, traditional fuzzy set theories struggle with the uncertainties inherent in these environments. This study addresses this gap by introducing the probabilistic p, q-rung orthopair fuzzy model, a novel extension that integrates probabilistic elements to improve precision and robustness in decision-making. Key contributions include the development of advanced aggregation operators, such as probabilistic weighted averaging and geometric operators, and their application in a multi-attribute decision-making algorithm. The model is validated through a case study on cloud service provider selection, demonstrating its effectiveness in supporting sustainable development and planning. The results show that the proposed model outperforms existing approaches, offering enhanced accuracy and reliability. This contribution advances decision-making frameworks in desktop cloud environments, fostering sustainability and improving the efficiency of daily office tasks.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"194 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546321","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

Energy-efficient real-time multi-workflow scheduling in container-based cloud

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-02-22 DOI: 10.1007/s10878-025-01265-8

Zaixing Sun, Hejiao Huang, Zhikai Li, Chonglin Gu

{"title":"Energy-efficient real-time multi-workflow scheduling in container-based cloud","authors":"Zaixing Sun, Hejiao Huang, Zhikai Li, Chonglin Gu","doi":"10.1007/s10878-025-01265-8","DOIUrl":"https://doi.org/10.1007/s10878-025-01265-8","url":null,"abstract":"Cloud computing has a powerful capability to handle a large number of tasks. However, this capability comes with significant energy requirements. It is critical to overcome the challenge of minimizing energy consumption within cloud service platforms without compromising service quality. In this paper, we propose a heuristic energy-saving scheduling algorithm, called Real-time Multi-workflow Energy-efficient Scheduling (RMES), which aims to minimize the total energy consumption in a container-based cloud. RMES schedules tasks in the most parallelized way to improve the resource utilization of the running machines in the cluster, thus reducing the time of the global process and saving energy. This paper also considers the affinity constraints between containers and machines, and RMES has the ability to satisfy the resource quantity and performance requirements of containers during the scheduling process. We introduce a re-scheduling mechanism that automatically adjusts the scheduling decisions of remaining tasks to account for the dynamic system states over time. The results show that RMES outperforms other scheduling algorithms in energy consumption and success rate. In the higher arrival rate scenario, the proposed algorithm saves energy consumption by more than 19.42%. The RMES approach can enhance the reliability and efficiency of scheduling systems.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"31 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143473554","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

Improved lower bound for estimating the number of defective items

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-02-20 DOI: 10.1007/s10878-025-01264-9

Nader H. Bshouty

{"title":"Improved lower bound for estimating the number of defective items","authors":"Nader H. Bshouty","doi":"10.1007/s10878-025-01264-9","DOIUrl":"https://doi.org/10.1007/s10878-025-01264-9","url":null,"abstract":"Consider a set of items, X, with a total of n items, among which a subset, denoted as (Isubseteq X), consists of defective items. In the context of group testing, a test is conducted on a subset of items Q, where (Q subset X). The result of this test is positive, yielding 1, if Q includes at least one defective item, that is if (Q cap I ne emptyset ). It is negative, yielding 0, if no defective items are present in Q. We introduce a novel method for deriving lower bounds in the context of non-adaptive randomized group testing. For any given constant j, any non-adaptive randomized algorithm that, with probability at least 2/3, estimates the number of defective items |I| within a constant factor requires at least $$Omega left( dfrac{log n}{log log {mathop {cdots }limits ^{j}}log n}right) $$tests. Our result almost matches the upper bound of (O(log n)) and addresses the open problem posed by Damaschke and Sheikh Muhammad in (Combinatorial Optimization and Applications - 4th International Conference, COCOA 2010, pp 117–130, 2010; Discrete Math Alg Appl 2(3):291–312, 2010). Furthermore, it enhances the previously established lower bound of (Omega (log n/log log n)) by Ron and Tsur (ACM Trans Comput Theory 8(4): 15:1–15:19, 2016), and independently by Bshouty (30th International Symposium on Algorithms and Computation, ISAAC 2019, LIPIcs, vol 149, pp 2:1–2:9, 2019). For estimation within a non-constant factor (alpha (n)), we show: If a constant j exists such that (alpha >{log log {mathop {cdots }limits ^{j}}log n}), then any non-adaptive randomized algorithm that, with probability at least 2/3, estimates the number of defective items |I| to within a factor (alpha ) requires at least $$Omega left( dfrac{log n}{log alpha }right) .$$In this case, the lower bound is tight.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462861","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 edge-vertex domination and weighted edge-vertex domination problem

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-02-20 DOI: 10.1007/s10878-025-01263-w

Peng Li, Xinyi Xue, Xingli Zhou

{"title":"The edge-vertex domination and weighted edge-vertex domination problem","authors":"Peng Li, Xinyi Xue, Xingli Zhou","doi":"10.1007/s10878-025-01263-w","DOIUrl":"https://doi.org/10.1007/s10878-025-01263-w","url":null,"abstract":"Consider a simple (edge weighted) graph (G = left( {V,E} right)) with (left| V right| = n) and (left| E right| = m). Let (xy in E). The domination of a vertex (z in V) by an edge (xy) is defined as (z) belonging to the closed neighborhood of either (x) or (y). An edge set (W) is considered as an edge-vertex dominating set of (G) if each vertex of (V) is dominated by some edge of (W). The (weighted) edge-vertex domination problem aims to find an edge-vertex dominating set of (G) with the minimum cardinality. Let (M subseteq V) and (N subseteq E). Given a positive integer (p), if a vertex (z) is dominated by (p) edges in set (N), then set (N) is called a (p) edge-vertex dominating set of graph (G) with respect to (M). This study investigates the edge-vertex domination problem and the (p) edge-vertex domination problem, presents an algorithm with a time complexity of (Oleft( {nm^{2} } right)) for solving the weighted edge-vertex domination problem on unit interval graphs. Moreover, algorithms have been developed with time complexities of (Oleft( {mlg m + pleft| M right| + n} right)) and (Oleft( {nleft| M right|} right)) for identifying a minimum (p) edge-vertex dominating set of an interval graph (G) and a tree (T), respectively, with respect to any subset (M subseteq V).","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"50 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462859","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 minimum orientable genus of the repeated Cartesian product of graphs

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-02-20 DOI: 10.1007/s10878-025-01266-7

Marietta Galea, John Baptist Gauci

引用次数: 0

Multiple identical serial-batch machines scheduling with release dates and submodular rejection penalties

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-02-20 DOI: 10.1007/s10878-025-01267-6

Zhichao Geng, Lingfa Lu

引用次数: 0

An $$L_2$$ regularization reduced quadratic surface support vector machine model

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-02-18 DOI: 10.1007/s10878-024-01250-7

Jiguang Wang, Fangfang Guo, Jie Shen

{"title":"An $$L_2$$ regularization reduced quadratic surface support vector machine model","authors":"Jiguang Wang, Fangfang Guo, Jie Shen","doi":"10.1007/s10878-024-01250-7","DOIUrl":"https://doi.org/10.1007/s10878-024-01250-7","url":null,"abstract":"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 term and the Hessian of the quadratic surface is reduced to a diagonal matrix. This simplification significantly reduces the number of decision variables and improves computational efficiency. The (L_1) loss function is used to transform the problem into a convex composite optimization problem. Then the transformed problem is solved by the Augmented Lagrange method and the non-smoothness of the subproblems is handled by the semi-smooth Newton algorithm. Numerical experiments on artificial and public benchmark datasets show that RQSSVM model not only inherits the superior performance of quadratic surface SVM for segmenting nonlinear surfaces, but also significantly improves the segmentation speed and efficiency.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"13 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143435176","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

Solving the optimal order quantity with unknown parameters for products with stock-dependent demand and variable holding cost rate

IF 1 4区数学

Journal of Combinatorial Optimization Pub Date : 2025-02-09 DOI: 10.1007/s10878-025-01260-z

Zhanbing Guo, Yejie Zhang

{"title":"Solving the optimal order quantity with unknown parameters for products with stock-dependent demand and variable holding cost rate","authors":"Zhanbing Guo, Yejie Zhang","doi":"10.1007/s10878-025-01260-z","DOIUrl":"https://doi.org/10.1007/s10878-025-01260-z","url":null,"abstract":"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, includes the following two merits when managing products with stock-dependent demand and variable holding cost rate. First, it is feasible even when the values of underlying parameters are unknown. Second, it is easy-to-implement as decisions are made via adaptively recalibrating the inputs of classical EOQ formula by observable variables in the previous period. Theoretical analysis and numerical example show that this two-stage AEOQ policy could obtain the optimal order quantity. Moreover, this two-stage AEOQ policy is robust to parameter misestimation, and performs better than the traditional solution method when the underlying parameters are volatile. Finally, it is shown that this two-stage AEOQ policy could be further simplified when the fixed ordering cost is negligible. Therefore, this study provides a feasible order policy when the exact values of underlying parameters are unable to gain or when the economic environment is volatile.","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"45 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375192","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