EURO Journal on Computational Optimization最新文献_第9页

Pareto front approximation through a multi-objective augmented Lagrangian method 基于多目标增广拉格朗日方法的Pareto前逼近

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2021.100008

Guido Cocchi , Matteo Lapucci , Pierluigi Mansueto

引用次数: 7

Robust flows with adaptive mitigation 具有自适应缓解的健壮流

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2020.100002

Heiner Ackermann , Erik Diessel , Sven O. Krumke

{"title":"Robust flows with adaptive mitigation","authors":"Heiner Ackermann , Erik Diessel , Sven O. Krumke","doi":"10.1016/j.ejco.2020.100002","DOIUrl":"https://doi.org/10.1016/j.ejco.2020.100002","url":null,"abstract":"<div><p>We consider an adjustable robust optimization problem arising in the area of supply chains: given sets of suppliers and demand nodes, we wish to find a flow that is robust with respect to failures of the suppliers. The objective is to determine a flow that minimizes the amount of shortage in the worst-case after an optimal mitigation has been performed. An optimal mitigation is an additional flow in the residual network that mitigates as much shortage at the demand sites as possible. For this problem we give a mathematical formulation, yielding a robust flow problem with three stages where the mitigation of the last stage can be chosen adaptively depending on the scenario. We show that already evaluating the robustness of a solution is <span><math><mi>NP</mi></math></span>-hard. For optimizing with respect to this <span><math><mi>NP</mi></math></span>-hard objective function, we compare three algorithms. Namely an algorithm based on iterative cut generation that solves medium-sized instances efficiently, a simple Outer Linearization Algorithm and a Scenario Enumeration algorithm. We illustrate the performance by numerical experiments. The results show that this instance of fully adjustable robust optimization problems can be solved exactly with a reasonable performance. We also describe possible extensions to the model and the algorithm.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"9 ","pages":"Article 100002"},"PeriodicalIF":2.4,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ejco.2020.100002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91979864","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: 1

Some contributions of Ailsa H. Land to the study of the traveling salesman problem 艾尔萨·h·兰德对旅行商问题研究的一些贡献

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2021.100018

Gilbert Laporte

引用次数: 1

The Solution of some 100-city Travelling Salesman Problems 近百个城市旅行商问题的求解

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2021.100017

A. Land

引用次数: 1

Quadratically adjustable robust linear optimization with inexact data via generalized S-lemma: Exact second-order cone program reformulations 基于广义s引理的非精确数据的二次可调鲁棒线性优化:精确二阶锥规划的重新表述

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2021.100019

V. Jeyakumar, G. Li, D. Woolnough

{"title":"Quadratically adjustable robust linear optimization with inexact data via generalized S-lemma: Exact second-order cone program reformulations","authors":"V. Jeyakumar, G. Li, D. Woolnough","doi":"10.1016/j.ejco.2021.100019","DOIUrl":"https://doi.org/10.1016/j.ejco.2021.100019","url":null,"abstract":"<div><p>Adjustable robust optimization allows for some variables to depend upon the uncertain data after its realization. However, the uncertainty is often not revealed exactly. Incorporating inexactness of the revealed data in the construction of ellipsoidal uncertainty sets, we present an exact second-order cone program reformulation for robust linear optimization problems with inexact data and quadratically adjustable variables. This is achieved by establishing a generalization of the celebrated S-lemma for a separable quadratic inequality system with at most one non-homogeneous function. It allows us to reformulate the resulting separable quadratic constraints over an intersection of two ellipsoids in terms of second-order cone constraints. We illustrate our results via numerical experiments on adjustable robust lot-sizing problems with demand uncertainty, showing improvements over corresponding problems with affinely adjustable variables as well as with exactly revealed data.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"9 ","pages":"Article 100019"},"PeriodicalIF":2.4,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192440621001465/pdfft?md5=a4dc90a6e60a07a7b22d11984e1bb230&pid=1-s2.0-S2192440621001465-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91979794","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: 3

The Steiner bi-objective shortest path problem Steiner双目标最短路径问题

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2021.100004

Hamza Ben Ticha , Nabil Absi , Dominique Feillet , Alain Quilliot

引用次数: 2

Recent advances in nonconvex semi-infinite programming: Applications and algorithms 非凸半无限规划的最新进展:应用与算法

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2021.100006

Hatim Djelassi , Alexander Mitsos , Oliver Stein

引用次数: 18

Mobility offer allocations in corporate settings 移动提供分配在企业设置

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2021.100010

Sebastian Knopp, Benjamin Biesinger, Matthias Prandtstetter

{"title":"Mobility offer allocations in corporate settings","authors":"Sebastian Knopp, Benjamin Biesinger, Matthias Prandtstetter","doi":"10.1016/j.ejco.2021.100010","DOIUrl":"https://doi.org/10.1016/j.ejco.2021.100010","url":null,"abstract":"<div><p>Corporate mobility is often based on a fixed assignment of vehicles to employees. Relaxing this fixation and including alternatives such as public transportation or taxis for business and private trips could increase fleet utilization and foster the use of battery electric vehicles. We introduce the <em>mobility offer allocation problem</em>as the core concept of a flexible booking system for corporate mobility. The problem is equivalent to interval scheduling on dedicated unrelated parallel machines. We show that the problem is NP-hard to approximate within any factor. We describe problem specific conflict graphs for representing and exploring the structure of feasible solutions. A characterization of all maximum cliques in these conflict graphs reveals symmetries which allow to formulate stronger integer linear programming models. We also present an adaptive large neighborhood search based approach which makes use of conflict graphs as well. In a computational study, the approaches are evaluated. It was found that greedy heuristics perform best if very tight run-time requirements are given, a solver for the integer linear programming model performs best on small and medium instances, and the adaptive large neighborhood search performs best on large instances.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"9 ","pages":"Article 100010"},"PeriodicalIF":2.4,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.ejco.2021.100010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92106931","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: 3

Presolving linear bilevel optimization problems 求解线性双层优化问题

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2021.100020

Thomas Kleinert , Julian Manns , Martin Schmidt , Dieter Weninger

{"title":"Presolving linear bilevel optimization problems","authors":"Thomas Kleinert , Julian Manns , Martin Schmidt , Dieter Weninger","doi":"10.1016/j.ejco.2021.100020","DOIUrl":"10.1016/j.ejco.2021.100020","url":null,"abstract":"<div><p>Linear bilevel optimization problems are known to be strongly NP-hard and the computational techniques to solve these problems are often motivated by techniques from single-level mixed-integer optimization. Thus, during the last years and decades many branch-and-bound methods, cutting planes, or heuristics have been proposed. On the other hand, there is almost no literature on presolving linear bilevel problems although presolve is a very important ingredient in state-of-the-art mixed-integer optimization solvers. In this paper, we carry over standard presolve techniques from single-level optimization to bilevel problems and show that this needs to be done with great caution since a naive application of well-known techniques does often not lead to correctly presolved bilevel models. Our numerical study shows that presolve can also be very beneficial for bilevel problems but also highlights that these methods have a more heterogeneous effect on the solution process compared to what is known from single-level optimization. As a side result, our numerical experiments reveal that there is an urgent need for better and more heterogeneous test instance libraries to further propel the field of computational bilevel optimization.</p></div>","PeriodicalId":51880,"journal":{"name":"EURO Journal on Computational Optimization","volume":"9 ","pages":"Article 100020"},"PeriodicalIF":2.4,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192440621001477/pdfft?md5=9e7ad6370cbef2e71f6e19e0e4213468&pid=1-s2.0-S2192440621001477-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54300226","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: 2

Two decades of blackbox optimization applications 二十年的黑箱优化应用

IF 2.4

EURO Journal on Computational Optimization Pub Date : 2021-01-01 DOI: 10.1016/j.ejco.2021.100011

Stéphane Alarie , Charles Audet , Aïmen E. Gheribi , Michael Kokkolaras , Sébastien Le Digabel

引用次数: 46