Journal of Global Optimization最新文献_第4页

A surrogate-assisted a priori multiobjective evolutionary algorithm for constrained multiobjective optimization problems 用于受约束多目标优化问题的代理辅助先验多目标进化算法

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-05-29 DOI: 10.1007/s10898-024-01387-z

Pouya Aghaei pour, Jussi Hakanen, Kaisa Miettinen

{"title":"A surrogate-assisted a priori multiobjective evolutionary algorithm for constrained multiobjective optimization problems","authors":"Pouya Aghaei pour, Jussi Hakanen, Kaisa Miettinen","doi":"10.1007/s10898-024-01387-z","DOIUrl":"https://doi.org/10.1007/s10898-024-01387-z","url":null,"abstract":"We consider multiobjective optimization problems with at least one computationally expensive constraint function and propose a novel surrogate-assisted evolutionary algorithm that can incorporate preference information given a priori. We employ Kriging models to approximate expensive objective and constraint functions, enabling us to introduce a new selection strategy that emphasizes the generation of feasible solutions throughout the optimization process. In our innovative model management, we perform expensive function evaluations to identify feasible solutions that best reflect the decision maker’s preferences provided before the process. To assess the performance of our proposed algorithm, we utilize two distinct parameterless performance indicators and compare them against existing algorithms from the literature using various real-world engineering and benchmark problems. Furthermore, we assemble new algorithms to analyze the effects of the selection strategy and the model management on the performance of the proposed algorithm. The results show that in most cases, our algorithm has a better performance than the assembled algorithms, especially when there is a restricted budget for expensive function evaluations.","PeriodicalId":15961,"journal":{"name":"Journal of Global Optimization","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141172451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Node selection through upper bounding local search methods in branch & bound solvers for NCOPs 在 NCOP 的分支与边界求解器中通过上界局部搜索方法选择节点

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-05-25 DOI: 10.1007/s10898-024-01403-2

Victor Reyes, Ignacio Araya

{"title":"Node selection through upper bounding local search methods in branch & bound solvers for NCOPs","authors":"Victor Reyes, Ignacio Araya","doi":"10.1007/s10898-024-01403-2","DOIUrl":"https://doi.org/10.1007/s10898-024-01403-2","url":null,"abstract":"Interval-based branch & bound solvers are commonly used for solving Nonlinear Continuous global Optimization Problems (NCOPs). In each iteration, the solver strategically chooses and processes a node within the search tree. The node is bisected and the two generated offspring nodes are processed by filtering methods. For each of these nodes, the solver also searches for new feasible solutions in order to update the best candidate solution. The cost of this solution is used for pruning non-optimal branches of the search tree. Thus, node selection and finding new solutions, stands as pivotal aspects in the functionality of these kind of solvers. The ability to find close-to-optimal solutions early in the search process may discard extensive non-optimal search space regions, thereby effectively reducing the overall size of the search tree. In this work, we propose three novel node selection algorithms that use the feasible solutions obtained through a cost-effective iterative method. Upon updating the best candidate solution, these algorithms strategically choose the node containing this solution for subsequent processing. The newly introduced strategies have been incorporated as node selection methods in a state-of-the-art branch & bound solver, showing promising results in a set of 57 benchmark instances.\u0000","PeriodicalId":15961,"journal":{"name":"Journal of Global Optimization","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141150599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 labeling of higher order Voronoi diagrams 高阶 Voronoi 图的边标注

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-05-21 DOI: 10.1007/s10898-024-01386-0

Mercè Claverol, Andrea de las Heras Parrilla, Clemens Huemer, Alejandra Martínez-Moraian

引用次数: 0

A revised monotonicity-based method for computing tight image enclosures of functions 基于单调性的计算函数紧图像包围的修订方法

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-05-16 DOI: 10.1007/s10898-024-01405-0

Ignacio Araya, Víctor Reyes

引用次数: 0

Dual optimality conditions for the difference of extended real valued increasing co-radiant functions 扩展实值递增共辐射函数差分的双重最优条件

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-05-11 DOI: 10.1007/s10898-024-01404-1

Mohammad Hossein Daryaei, Hossein Mohebi

引用次数: 0

On polling directions for randomized direct-search approaches: application to beam angle optimization in intensity-modulated proton therapy 随机直接搜索方法的投票方向：应用于强度调制质子疗法中的射束角优化

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-05-10 DOI: 10.1007/s10898-024-01400-5

H. Rocha, J. Dias

{"title":"On polling directions for randomized direct-search approaches: application to beam angle optimization in intensity-modulated proton therapy","authors":"H. Rocha, J. Dias","doi":"10.1007/s10898-024-01400-5","DOIUrl":"https://doi.org/10.1007/s10898-024-01400-5","url":null,"abstract":"Deterministic direct-search methods have been successfully used to address real-world challenging optimization problems, including the beam angle optimization (BAO) problem in radiation therapy treatment planning. BAO is a highly non-convex optimization problem typically treated as the optimization of an expensive multi-modal black-box function which results in a computationally time consuming procedure. For the recently available modalities of radiation therapy with protons (instead of photons) further efficiency in terms of computational time is required despite the success of the different strategies developed to accelerate BAO approaches. Introducing randomization into otherwise deterministic direct-search approaches has been shown to lead to excellent computational performance, particularly when considering a reduced number (as low as two) of random poll directions at each iteration. In this study several randomized direct-search strategies are tested considering different sets of polling directions. Results obtained using a prostate and a head-and-neck cancer cases confirmed the high-quality results obtained by deterministic direct-search methods. Randomized strategies using a reduced number of polling directions showed difficulties for the higher dimensional search space (head-and-neck) and, despite the excellent mean results for the prostate cancer case, outliers were observed, a result that is often ignored in the literature. While, for general global optimization problems, mean results (or obtaining the global optimum once) might be enough for assessing the performance of the randomized method, in real-world problems one should not disregard the worst-case scenario and beware of the possibility of poor results since, many times, it is only possible to run the optimization problem once. This is even more important in healthcare applications where the mean patient does not exist and the best treatment possible must be assured for every patient.","PeriodicalId":15961,"journal":{"name":"Journal of Global Optimization","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140937382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Rectilinear convex hull of points in 3D and applications 三维中点的直线凸壳及其应用

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-05-04 DOI: 10.1007/s10898-024-01402-3

Pablo Pérez-Lantero, Carlos Seara, Jorge Urrutia

引用次数: 0

Social equity in international environmental agreements 国际环境协定中的社会公平

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-04-29 DOI: 10.1007/s10898-024-01368-2

Chiara Donnini, Armando Sacco

{"title":"Social equity in international environmental agreements","authors":"Chiara Donnini, Armando Sacco","doi":"10.1007/s10898-024-01368-2","DOIUrl":"https://doi.org/10.1007/s10898-024-01368-2","url":null,"abstract":"The aim of this paper is to investigate the problem of designing and building International Environmental Agreements (IEAs) taking into account some normative properties. We consider n asymmetric countries of the world, each one generating a quantity of pollutant emissions from the production of goods and services. We assume that individual emissions yield private benefits and negative externalities affecting all countries. To determine its own level of pollution, each state conducts a cost-benefit analysis. The absence of a supranational entity imposing emissions reduction makes IEAs based on voluntary participation. Examining the standard static non-cooperative game-theoretical model of coalition formation, we discover that the resulting emissions allocations might not be equitable à la Foley. It means that there might exist at least one player preferring to implement some other agent’s strategic plan instead of to play her own strategy. With the goal of studying whether equity, at least among coalesced countries, may be a criterion leading to social improvement, we introduce a new optimization rule. We require that members of an environmental coalition have to solve the maximization problem subject to the constraint imposing that they do not envy each other. Analyzing the particular case of two-player games, we get that, when countries are, in a sense, not too different from each other, our new mechanism endogenously induces social equity. By imposing a suitable total emission cap, the same results extend to all those games where our and standard solutions coexist and are different.\u0000","PeriodicalId":15961,"journal":{"name":"Journal of Global Optimization","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140831343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Subspace Newton method for sparse group $$ell _0$$ optimization problem 稀疏组 $$ell _0$$ 优化问题的子空间牛顿法

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-04-29 DOI: 10.1007/s10898-024-01396-y

Shichen Liao, Congying Han, Tiande Guo, Bonan Li

{"title":"Subspace Newton method for sparse group $$ell _0$$ optimization problem","authors":"Shichen Liao, Congying Han, Tiande Guo, Bonan Li","doi":"10.1007/s10898-024-01396-y","DOIUrl":"https://doi.org/10.1007/s10898-024-01396-y","url":null,"abstract":"This paper investigates sparse optimization problems characterized by a sparse group structure, where element- and group-level sparsity are jointly taken into account. This particular optimization model has exhibited notable efficacy in tasks such as feature selection, parameter estimation, and the advancement of model interpretability. Central to our study is the scrutiny of the (ell _0) and (ell _{2,0}) norm regularization model, which, in comparison to alternative surrogate formulations, presents formidable computational challenges. We embark on our study by conducting the analysis of the optimality conditions of the sparse group optimization problem, leveraging the notion of a (gamma )-stationary point, whose linkage to local and global minimizer is established. In a subsequent facet of our study, we develop a novel subspace Newton algorithm for sparse group (ell _0) optimization problem and prove its global convergence property as well as local second-order convergence rate. Experimental results reveal the superlative performance of our algorithm in terms of both precision and computational expediency, thereby outperforming several state-of-the-art solvers.","PeriodicalId":15961,"journal":{"name":"Journal of Global Optimization","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140831341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Tighter bound estimation for efficient biquadratic optimization over unit spheres 单位球上高效二次优化的更严格边界估计

IF 1.8 3区数学

Journal of Global Optimization Pub Date : 2024-04-29 DOI: 10.1007/s10898-024-01401-4

Shigui Li, Linzhang Lu, Xing Qiu, Zhen Chen, Delu Zeng

{"title":"Tighter bound estimation for efficient biquadratic optimization over unit spheres","authors":"Shigui Li, Linzhang Lu, Xing Qiu, Zhen Chen, Delu Zeng","doi":"10.1007/s10898-024-01401-4","DOIUrl":"https://doi.org/10.1007/s10898-024-01401-4","url":null,"abstract":"Bi-quadratic programming over unit spheres is a fundamental problem in quantum mechanics introduced by pioneer work of Einstein, Schrödinger, and others. It has been shown to be NP-hard; so it must be solve by efficient heuristic algorithms such as the block improvement method (BIM). This paper focuses on the maximization of bi-quadratic forms with nonnegative coefficient tensors, which leads to a rank-one approximation problem that is equivalent to computing the M-spectral radius and its corresponding eigenvectors. Specifically, we propose a tight upper bound of the M-spectral radius for nonnegative fourth-order partially symmetric (PS) tensors. This bound, serving as an improved shift parameter, significantly enhances the convergence speed of BIM while maintaining computational complexity aligned with the initial shift parameter of BIM. Moreover, we elucidate that the computation cost of such upper bound can be further simplified for certain sets and delve into the nature of these sets. Building on the insights gained from the proposed bounds, we derive the exact solutions of the M-spectral radius and its corresponding M-eigenvectors for certain classes of fourth-order PS-tensors and discuss the nature of this specific category. Lastly, as a practical application, we introduce a testable sufficient condition for the strong ellipticity in the field of solid mechanics. Numerical experiments demonstrate the utility of the proposed results.","PeriodicalId":15961,"journal":{"name":"Journal of Global Optimization","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140831144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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