EURO Journal on Computational Optimization最新文献_第2页

On improvements of multi-objective branch and bound 论多目标分支与约束的改进

IF 2.6

EURO Journal on Computational Optimization Pub Date : 2024-01-01 DOI: 10.1016/j.ejco.2024.100099

Julius Bauß , Sophie N. Parragh , Michael Stiglmayr

引用次数: 0

Resource constraint scheduling on two dedicated machines: Application to avionics 两台专用机上的资源约束调度：航空电子设备的应用

IF 2.6

EURO Journal on Computational Optimization Pub Date : 2024-01-01 DOI: 10.1016/j.ejco.2024.100093

Mesli-Kesraoui Ouissem , Ledreck Loic , Grolleau Emmanuel , Kesraoui Soraya , Berruet Pascal , Ouhammou Yassine , Girard Patrick

{"title":"Resource constraint scheduling on two dedicated machines: Application to avionics","authors":"Mesli-Kesraoui Ouissem , Ledreck Loic , Grolleau Emmanuel , Kesraoui Soraya , Berruet Pascal , Ouhammou Yassine , Girard Patrick","doi":"10.1016/j.ejco.2024.100093","DOIUrl":"10.1016/j.ejco.2024.100093","url":null,"abstract":"<div><p>In civil aircraft, two partially redundant hydraulic circuits typically power various systems. During assembly, a critical phase involves simultaneously rinsing and purging these hydraulic circuits using loops. Precedence constraints are necessary to prevent the recontamination of already rinsed loops, leading to increased rinsing time. This paper presents this problem as a unique instance of the Resource Constrained Parallel Machine Scheduling Problem, where each circuit represents a machine, pipe loops to be rinsed represent jobs, and machines share a hydraulic power source. For two dedicated processors and a single resource, an optimal schedule minimizing the makespan can be generated in polynomial time. However, due to the requirement of rinsing certain pipe loops on a circuit before others, there are precedence constraints between some jobs within the same circuit. By employing a reduction of the 3-partition problem, we demonstrate that this situation results in a problem that is NP-hard in the strong sense. We evaluate several Mixed-Integer Linear Programming and Constraint Programming formulations of the problem, using Cplex, CPO, Gurobi, and Z3, against several proposed heuristics. Given that the size of the instances we need to solve exceeds what can be solved in acceptable time by solvers, we propose a heuristic and compare its performance with the optimum.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"12 ","pages":"Article 100093"},"PeriodicalIF":2.6,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192440624000108/pdfft?md5=609c1088bd5eb7a592a2eadcb5134f21&pid=1-s2.0-S2192440624000108-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141407096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A variable metric proximal stochastic gradient method: An application to classification problems 可变度量近似随机梯度法：分类问题的应用

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2024-01-01 DOI: 10.1016/j.ejco.2024.100088

Pasquale Cascarano , Giorgia Franchini , Erich Kobler , Federica Porta , Andrea Sebastiani

{"title":"A variable metric proximal stochastic gradient method: An application to classification problems","authors":"Pasquale Cascarano , Giorgia Franchini , Erich Kobler , Federica Porta , Andrea Sebastiani","doi":"10.1016/j.ejco.2024.100088","DOIUrl":"https://doi.org/10.1016/j.ejco.2024.100088","url":null,"abstract":"<div><p>Due to the continued success of machine learning and deep learning in particular, supervised classification problems are ubiquitous in numerous scientific fields. Training these models typically involves the minimization of the empirical risk over large data sets along with a possibly non-differentiable regularization. In this paper, we introduce a stochastic gradient method for the considered classification problem. To control the variance of the objective's gradients, we use an automatic sample size selection along with a variable metric to precondition the stochastic gradient directions. Further, we utilize a non-monotone line search to automatize step size selection. Convergence results are provided for both convex and non-convex objective functions. Extensive numerical experiments verify that the suggested approach performs on par with state-of-the-art methods for training both statistical models for binary classification and artificial neural networks for multi-class image classification. The code is publicly available at <span>https://github.com/koblererich/lisavm</span><svg><path></path></svg>.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"12 ","pages":"Article 100088"},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192440624000054/pdfft?md5=738f38c0990532c2e5eec98c42a34bd4&pid=1-s2.0-S2192440624000054-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140647201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of experiments for the stochastic unit commitment with economic dispatch models 采用经济调度模型的随机机组承诺试验设计

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2024-01-01 DOI: 10.1016/j.ejco.2024.100089

Nahal Sakhavand , Jay Rosenberger , Victoria C.P. Chen , Harsha Gangammanavar

{"title":"Design of experiments for the stochastic unit commitment with economic dispatch models","authors":"Nahal Sakhavand , Jay Rosenberger , Victoria C.P. Chen , Harsha Gangammanavar","doi":"10.1016/j.ejco.2024.100089","DOIUrl":"https://doi.org/10.1016/j.ejco.2024.100089","url":null,"abstract":"<div><p>We develop a Design and Analysis of the Computer Experiments (DACE) approach to the stochastic unit commitment problem for power systems with significant renewable integration. For this purpose, we use a two-stage stochastic programming formulation of the stochastic unit commitment-economic dispatch problem. Typically, a sample average approximation of the true problem is solved using a cutting plane method (such as the L-shaped method) or scenario decomposition (such as Progressive Hedging) algorithms. However, when the number of scenarios increases, these solution methods become computationally prohibitive. To address this challenge, we develop a novel DACE approach that exploits the structure of the first-stage unit commitment decision space in a design of experiments, uses features based upon solar generation, and trains a multivariate adaptive regression splines model to approximate the second stage of the stochastic unit commitment-economic dispatch problem. We conduct experiments on two modified IEEE-57 and IEEE-118 test systems and assess the quality of the solutions obtained from both the DACE and the L-shaped methods in a replicated procedure. The results obtained from this approach attest to the significant improvement in the computational performance of the DACE approach over the traditional L-shaped method.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"12 ","pages":"Article 100089"},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192440624000066/pdfft?md5=734ce10eb038b678d854fede2426d31a&pid=1-s2.0-S2192440624000066-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140906327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A two-point heuristic to calculate the stepsize in subgradient method with application to a network design problem 计算子梯度法步长的两点启发式，并应用于网络设计问题

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2024-01-01 DOI: 10.1016/j.ejco.2024.100092

F. Carrabs , M. Gaudioso , G. Miglionico

{"title":"A two-point heuristic to calculate the stepsize in subgradient method with application to a network design problem","authors":"F. Carrabs , M. Gaudioso , G. Miglionico","doi":"10.1016/j.ejco.2024.100092","DOIUrl":"10.1016/j.ejco.2024.100092","url":null,"abstract":"<div><p>We introduce a heuristic rule for calculating the stepsize in the subgradient method for unconstrained convex nonsmooth optimization which, unlike the classic approach, is based on retaining some information from previous iteration. The rule is inspired by the well known two-point stepsize by Barzilai and Borwein (BB) <span>[6]</span> for smooth optimization and it coincides with (BB) in case the function to be minimised is convex quadratic.</p><p>Under the use of appropriate safeguards we demonstrate that the method terminates at a point that satisfies an approximate optimality condition.</p><p>The proposed approach is tested in the framework of Lagrangian relaxation for integer linear programming where the Lagrangian dual requires maximization of a concave and nonsmooth (piecewise affine) function. In particular we focus on the relaxation of the Minimum Spanning Tree problem with Conflicting Edge Pairs (MSTC). Comparison with classic subgradient method is presented. The results on some widely used academic test problems are provided too.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"12 ","pages":"Article 100092"},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192440624000091/pdfft?md5=8c30a5148ef2dc0e6dc45f8a7bbd0259&pid=1-s2.0-S2192440624000091-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141130830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revisiting a Cornuéjols-Nemhauser-Wolsey formulation for the p-median problem 重新审视 p 中值问题的 Cornuéjols-Nemhauser-Wolsey 公式

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-12-14 DOI: 10.1016/j.ejco.2023.100081

Agostinho Agra , Cristina Requejo

{"title":"Revisiting a Cornuéjols-Nemhauser-Wolsey formulation for the p-median problem","authors":"Agostinho Agra , Cristina Requejo","doi":"10.1016/j.ejco.2023.100081","DOIUrl":"https://doi.org/10.1016/j.ejco.2023.100081","url":null,"abstract":"<div><p>We revisit a formulation for the simple plant facility location and p-median problems introduced by Cornuéjols, Nemhauser and Wolsey (1980). Despite being the smallest known formulation regarding the number of variables, this formulation is barely used or cited in the literature. Here, we reintroduce the formulation for the p-median problem from a different perspective, resulting from the intersection of a selection problem with an additional family of optimality constraints to define the costs correctly. An alternative proof that the linear relaxation of the formulation is equivalent to the linear relaxation of the well-known classical formulation is provided. By exploring the optimality constraints we discuss approaches to derive bounds for large-size instances. These approaches are based on relaxations obtained by eliminating optimality constraints and can be seen as a simple matheuristic to solve large size instances. In particular, we characterize relaxations which provide the optimal solution, and therefore, can be seen as new formulations for the p-median problem. Computational tests are reported showing that the renewed formulation can be used efficiently to solve p-median instances.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"12 ","pages":"Article 100081"},"PeriodicalIF":2.4,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192440623000254/pdfft?md5=0bcc422776e1511a6efd5d524a292e3a&pid=1-s2.0-S2192440623000254-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138769860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2022.100052

Hemen Sanati, Ghasem Moslehi, Mohammad Reisi-Nafchi

{"title":"Unrelated parallel machine energy-efficient scheduling considering sequence-dependent setup times and time-of-use electricity tariffs","authors":"Hemen Sanati, Ghasem Moslehi, Mohammad Reisi-Nafchi","doi":"10.1016/j.ejco.2022.100052","DOIUrl":"10.1016/j.ejco.2022.100052","url":null,"abstract":"<div><p>Given that about half of the produced energy in the world is consumed in industries, there has been an increasing concern about optimizing energy consumption in manufacturing sectors. As one of the most effective ways, proper production scheduling to reduce energy consumption is of crucial importance among researchers and manufacturers. This paper addresses an unrelated parallel machine energy-efficient scheduling problem with sequence-dependent setup times by considering different energy consumption tariffs. The setup times are studied in two modes: disjointed from/jointed to processing time. For each one of these problems, two mixed-integer linear programming models have been formulated. The presented models for the problem with setup time disjointed from processing time can solve up to 16 machines and 45 jobs. In contrast, this capability is changed to 20 machines and 40 jobs for processing time jointed to the setup time problem. Furthermore, a fix and relax heuristic algorithm is presented for large-size instances, which can solve instances of up to 20 machines and 100 jobs for each of the two considered problems.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"11 ","pages":"Article 100052"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48398291","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

The missing Moore graph as an optimization problem 缺失摩尔图作为优化问题

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100060

Derek H. Smith , Roberto Montemanni

引用次数: 0

The Weber problem in logistic and services networks under congestion 拥挤条件下物流服务网络中的韦伯问题

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2022.100056

Vanessa Lange , Hans Daduna

引用次数: 0

An exact algorithm for the static pricing problem under discrete mixed logit demand 离散混合对数需求下静态定价问题的精确算法

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2023-01-01 DOI: 10.1016/j.ejco.2023.100073

Ahmadreza Marandi , Virginie Lurkin

引用次数: 0