EURO Journal on Computational Optimization最新文献_第4页

Hierarchical distributed optimization of constraint-coupled convex and mixed-integer programs using approximations of the dual function 基于对偶函数逼近的约束耦合凸和混合整数规划的分层分布优化

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100058

Vassilios Yfantis , Simon Wenzel , Achim Wagner , Martin Ruskowski , Sebastian Engell

{"title":"Hierarchical distributed optimization of constraint-coupled convex and mixed-integer programs using approximations of the dual function","authors":"Vassilios Yfantis , Simon Wenzel , Achim Wagner , Martin Ruskowski , Sebastian Engell","doi":"10.1016/j.ejco.2023.100058","DOIUrl":"10.1016/j.ejco.2023.100058","url":null,"abstract":"<div><p>In this paper, two new algorithms for dual decomposition-based distributed optimization are presented. Both algorithms rely on the quadratic approximation of the dual function of the primal optimization problem. The dual variables are updated in each iteration through a maximization of the approximated dual function. The first algorithm approximates the dual function by solving a regression problem, based on the values of the dual function collected from previous iterations. The second algorithm updates the parameters of the quadratic approximation via a quasi-Newton scheme. Both algorithms employ step size constraints for the update of the dual variables. Furthermore, the subgradients from previous iterations are stored in order to construct cutting planes, similar to bundle methods for nonsmooth optimization. However, instead of using the cutting planes to formulate a piece-wise linear over-approximation of the dual function, they are used to construct valid inequalities for the update step. In order to demonstrate the efficiency of the algorithms, they are evaluated on a large set of constrained quadratic, convex and mixed-integer benchmark problems and compared to the subgradient method, the bundle trust method, the alternating direction method of multipliers and the quadratic approximation coordination algorithm. The results show that the proposed algorithms perform better than the compared algorithms both in terms of the required number of iterations and in the number of solved benchmark problems in most cases.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"11 ","pages":"Article 100058"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44992580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A mixed-integer exponential cone programming formulation for feature subset selection in logistic regression 逻辑回归中特征子集选择的混合整数指数锥规划公式

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100069

Sahand Asgharieh Ahari , Burak Kocuk

{"title":"A mixed-integer exponential cone programming formulation for feature subset selection in logistic regression","authors":"Sahand Asgharieh Ahari , Burak Kocuk","doi":"10.1016/j.ejco.2023.100069","DOIUrl":"10.1016/j.ejco.2023.100069","url":null,"abstract":"<div><p>Logistic regression is one of the widely-used classification tools to construct prediction models. For datasets with a large number of features, feature subset selection methods are considered to obtain accurate and interpretable prediction models, in which irrelevant and redundant features are removed. In this paper, we address the problem of <em>feature subset selection in logistic regression</em> using modern optimization techniques. To this end, we formulate this problem as a mixed-integer exponential cone program (MIEXP). To the best of our knowledge, this is the first time both nonlinear and discrete aspects of the underlying problem are fully considered within an exact optimization framework. We derive different versions of the MIEXP model by the means of regularization and goodness of fit measures including Akaike Information Criterion and Bayesian Information Criterion. Finally, we solve our MIEXP models using the solver <em>MOSEK</em> and evaluate the performance of our different versions over a set of toy examples and benchmark datasets. The results show that our approach is quite successful in obtaining accurate and interpretable prediction models compared to other methods from the literature.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"11 ","pages":"Article 100069"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44435816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A variational approach for supply chain networks with environmental interests 考虑环境利益的供应链网络的变分方法

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100075

Gabriella Colajanni, Patrizia Daniele, Daniele Sciacca

{"title":"A variational approach for supply chain networks with environmental interests","authors":"Gabriella Colajanni, Patrizia Daniele, Daniele Sciacca","doi":"10.1016/j.ejco.2023.100075","DOIUrl":"10.1016/j.ejco.2023.100075","url":null,"abstract":"<div><p>Nowadays, the supply chain networks, consisting of different tiers of decision-makers, provide an effective framework for the production, the distribution, and the consumption of goods. In this paper we propose a supply chain network optimization model where manufacturers, retailers and consumers in the demand markets have a degree of interest in environmental sustainability. The manufacturers can improve their energy level (assumed as variables), aim to minimize their environmental emissions (for production and transport) and can also establish the amount of quantity of the production waste to dispose in a eco-sustainable way. The retailers, who are also profit-maximizers, aim to minimize their environmental emissions (which depend on the chosen shipping methods). The consumers at demand markets make their own choices according to the prices and to their degree of aversion to the environmental emissions. We describe the behavior of each decision-maker and we present the mathematical model for each of them, deriving the variational inequality problems. Furthermore, we derive a unique variational inequality formulation for the entire network for whose solution an existence and uniqueness result is obtained. Finally, we illustrate some numerical simulations that highlight how the use of UAVs and the presence of waste sorting centers in the supply chain reduce environmental emissions and related costs.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"11 ","pages":"Article 100075"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46440929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On two symmetric Dai-Kou type schemes for constrained monotone equations with image recovery application 具有图像恢复应用的约束单调方程的两种对称Dai-Kou型格式

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100057

Kabiru Ahmed , Mohammed Yusuf Waziri , Abubakar Sani Halilu , Salisu Murtala

{"title":"On two symmetric Dai-Kou type schemes for constrained monotone equations with image recovery application","authors":"Kabiru Ahmed , Mohammed Yusuf Waziri , Abubakar Sani Halilu , Salisu Murtala","doi":"10.1016/j.ejco.2023.100057","DOIUrl":"10.1016/j.ejco.2023.100057","url":null,"abstract":"<div><p>The Dai-Kou method Dai and Kou (2013), <span>[12]</span> is efficient for solving unconstrained optimization problems. However, its modified variants are quite rare for constrained nonlinear monotone equations. In an attempt to address this, two adaptive versions of the scheme with new and efficient parameter choices are presented in this paper. The schemes are obtained by analyzing eigenvalues of a modified Dai-Kou iteration matrix and constructing two new directions, which are used in the scheme's algorithms. The new methods are derivative-free, which is an attribute required for handling problems with very large dimensions. Both methods also satisfy the required condition for analyzing global convergence in the literature. By applying mild conditions, it is shown that the schemes are globally convergent and description of their effectiveness is achieved through experiments with four effective schemes for solving constrained nonlinear monotone equations. Furthermore, the methods are applied to recover images that are contaminated by impulse noise in compressed sensing.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"11 ","pages":"Article 100057"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46322938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

The Marguerite Frank Award for the best EJCO paper 2022 2022年最佳EJCO论文的玛格丽特弗兰克奖

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100065

Immanuel Bomze (Editor-in-Chief)

引用次数: 0

A framework using nested partitions algorithm for convergence analysis of population distribution-based methods 基于嵌套划分算法的人口分布方法收敛性分析框架

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100067

Majid H.M. Chauhdry

{"title":"A framework using nested partitions algorithm for convergence analysis of population distribution-based methods","authors":"Majid H.M. Chauhdry","doi":"10.1016/j.ejco.2023.100067","DOIUrl":"10.1016/j.ejco.2023.100067","url":null,"abstract":"<div><p>Stochastic optimization algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), estimation of distribution algorithms (EDAs), and nested partitions algorithm (NPA) are used in many problems including nonlinear model predictive control and task assignment. Some of these algorithms, however, lack global convergence guarantee such as PSO, or require strict convergence assumptions such as NPA. To enhance these methods in terms of convergence, a common underlying framework towards representing the seemingly unrelated methods is established as the updating of the distribution of the population through iterative sampling, and the methods that fit into this framework are called <em>population distribution-based methods</em>. Global convergence conditions for this framework are innovatively developed by building a shadow NPA structure for the population evolution process. The result is generic and is capable of analyzing convergence of many methods including GA, PSO, EDA, and NPA. It can be further exploited to improve convergence by modifying these methods. The existing and modified variants of these methods are then applied to case studies to show the improvement.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"11 ","pages":"Article 100067"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47575572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Large-step predictor-corrector interior point method for sufficient linear complementarity problems based on the algebraic equivalent transformation 基于代数等价变换的充分线性互补问题的大步长预测校正内点法

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100072

Tibor Illés , Petra Renáta Rigó , Roland Török

{"title":"Large-step predictor-corrector interior point method for sufficient linear complementarity problems based on the algebraic equivalent transformation","authors":"Tibor Illés , Petra Renáta Rigó , Roland Török","doi":"10.1016/j.ejco.2023.100072","DOIUrl":"10.1016/j.ejco.2023.100072","url":null,"abstract":"<div><p>We introduce a new predictor-corrector interior-point algorithm for solving <span><math><msub><mrow><mi>P</mi></mrow><mrow><mo>⁎</mo></mrow></msub><mo>(</mo><mi>κ</mi><mo>)</mo></math></span>-linear complementarity problems which works in a wide neighbourhood of the central path. We use the technique of algebraic equivalent transformation of the centering equations of the central path system. In this technique, we apply the function <span><math><mi>φ</mi><mo>(</mo><mi>t</mi><mo>)</mo><mo>=</mo><msqrt><mrow><mi>t</mi></mrow></msqrt></math></span> in order to obtain the new search directions. We define the new wide neighbourhood <span><math><msub><mrow><mi>D</mi></mrow><mrow><mi>φ</mi></mrow></msub></math></span>. In this way, we obtain the first interior-point method, where not only the central path system is transformed, but the definition of the neighbourhood is also modified taking into consideration the algebraic equivalent transformation technique. This gives a new direction in the research of interior-point algorithms. We prove that the interior-point method has <span><math><mi>O</mi><mrow><mo>(</mo><mo>(</mo><mn>1</mn><mo>+</mo><mi>κ</mi><mo>)</mo><mi>n</mi><mi>log</mi><mo>⁡</mo><mrow><mo>(</mo><mfrac><mrow><msup><mrow><mo>(</mo><msup><mrow><mi>x</mi></mrow><mrow><mn>0</mn></mrow></msup><mo>)</mo></mrow><mrow><mi>T</mi></mrow></msup><msup><mrow><mi>s</mi></mrow><mrow><mn>0</mn></mrow></msup></mrow><mrow><mi>ϵ</mi></mrow></mfrac><mo>)</mo></mrow><mo>)</mo></mrow></math></span> iteration complexity. Furthermore, we show the efficiency of the proposed predictor-corrector algorithm by providing numerical results. To our best knowledge, this is the first predictor-corrector interior-point algorithm which works in the <span><math><msub><mrow><mi>D</mi></mrow><mrow><mi>φ</mi></mrow></msub></math></span> neighbourhood using <span><math><mi>φ</mi><mo>(</mo><mi>t</mi><mo>)</mo><mo>=</mo><msqrt><mrow><mi>t</mi></mrow></msqrt></math></span>.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"11 ","pages":"Article 100072"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49251533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A conceptually simple algorithm for the capacitated location-routing problem 一种概念简单的电容定位路由算法

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100063

Maximilian Löffler, Enrico Bartolini, Michael Schneider

{"title":"A conceptually simple algorithm for the capacitated location-routing problem","authors":"Maximilian Löffler, Enrico Bartolini, Michael Schneider","doi":"10.1016/j.ejco.2023.100063","DOIUrl":"10.1016/j.ejco.2023.100063","url":null,"abstract":"<div><p>Location-routing problems (LRPs) jointly optimize the location of depots and the routing of vehicles. The most studied LRP variant, the capacitated LRP (CLRP), has been addressed by a large number of metaheuristic approaches. These methods often decompose the problem into a location stage to determine a promising depot configuration and a routing stage, in which a vehicle-routing problem is solved to assess the quality of the previously determined depot configuration. Unfortunately, the CLRP literature does not shed much light on the important question which algorithmic features have the biggest influence on the solution quality and runtime of such heuristics. The purpose of this paper is to propose a conceptually simple (yet reasonably effective) heuristic for the CLRP and to provide some insights on the design of successful metaheuristics for this problem. Our algorithm is a hybrid combining (i) a GRASP phase that uses a variable neighborhood descent for local improvement in the location stage, and (ii) a variable neighborhood search in the routing stage. We analyze the impact of the algorithmic components on solution quality and runtime. In addition, we find that the suboptimal routing solutions used to assess the quality of the investigated depot configurations in tendency lead to depot configurations with too many open depots. We propose a depot configuration refinement phase that alleviates this drawback, and we show that this algorithmic component significantly contributes to the solution quality of our method, enabling it to provide reasonable results in comparison to the state-of-the-art methods from the literature.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"11 ","pages":"Article 100063"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49558632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

International migrant flows: Coalition formation among countries and social welfare 国际移民流动：国家间联盟的形成与社会福利

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100062

Mauro Passacantando , Fabio Raciti , Anna Nagurney

引用次数: 0

Experimentation with Benders decomposition for solving the two-timescale stochastic generation capacity expansion problem Benders分解求解两时间尺度随机发电容量扩展问题的实验

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100059

Goran Vojvodic , Luis J. Novoa , Ahmad I. Jarrah

{"title":"Experimentation with Benders decomposition for solving the two-timescale stochastic generation capacity expansion problem","authors":"Goran Vojvodic , Luis J. Novoa , Ahmad I. Jarrah","doi":"10.1016/j.ejco.2023.100059","DOIUrl":"10.1016/j.ejco.2023.100059","url":null,"abstract":"<div><p>The main purpose of solving a classical generation capacity expansion problem is to ensure that, in the medium- to long-term time frame, the electric utility has enough capacity available to reliably satisfy the demand for electricity from its customers. However, the ability to operate the newly built power plants also has to be considered. Operation of these plants could be curtailed by fuel availability, environmental constraints, or intermittency of renewable generation. This suggests that when generation capacity expansion problems are solved, along with the yearly timescale necessary to capture the long-term effect of the decisions, it is necessary to include a timescale granular enough to represent operations of generators with a credible fidelity. Additionally, given that the time horizon for a capacity expansion model is long, stochastic modeling of key parameters may generate more insightful, realistic, and judicious results. In the current model, we allow the demand for electricity and natural gas to behave stochastically. Together with the dual timescales, the randomness results in a large problem that is challenging to solve. In this paper, we experiment with synergistically combining elements of several methods that are, for the most part, based on Benders decomposition and construct an algorithm which allows us to find near-optimal solutions to the problem with reasonable run times.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"11 ","pages":"Article 100059"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46676316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0