INFORMS journal on optimization最新文献_第4页

Editorial Board 编辑委员会

INFORMS journal on optimization Pub Date : 2021-07-01 DOI: 10.1287/ijoo.2021.eb.v3n3

引用次数: 0

A Prescriptive Machine-Learning Framework to the Price-Setting Newsvendor Problem 报贩定价问题的规定性机器学习框架

INFORMS journal on optimization Pub Date : 2021-04-09 DOI: 10.1287/IJOO.2019.0046

P. Harsha, R. Natarajan, D. Subramanian

引用次数: 6

Algorithms for Difference-of-Convex Programs Based on Difference-of-Moreau-Envelopes Smoothing 基于差分包络平滑的凸差分规划算法

INFORMS journal on optimization Pub Date : 2021-04-03 DOI: 10.1287/ijoo.2022.0087

Kaizhao Sun, X. Sun

{"title":"Algorithms for Difference-of-Convex Programs Based on Difference-of-Moreau-Envelopes Smoothing","authors":"Kaizhao Sun, X. Sun","doi":"10.1287/ijoo.2022.0087","DOIUrl":"https://doi.org/10.1287/ijoo.2022.0087","url":null,"abstract":"In this paper, we consider minimization of a difference-of-convex (DC) function with and without linear equality constraints. We first study a smooth approximation of a generic DC function, termed difference-of-Moreau-envelopes (DME) smoothing, where both components of the DC function are replaced by their respective Moreau envelopes. The resulting smooth approximation is shown to be Lipschitz differentiable, capture stationary points, local, and global minima of the original DC function, and enjoy some growth conditions, such as level-boundedness and coercivity, for broad classes of DC functions. For a smoothed DC program without linear constraints, it is shown that the classic gradient descent method and an inexact variant converge to a stationary solution of the original DC function in the limit with a rate of [Formula: see text], where K is the number of proximal evaluations of both components. Furthermore, when the DC program is explicitly constrained in an affine subspace, we combine the smoothing technique with the augmented Lagrangian function and derive two variants of the augmented Lagrangian method (ALM), named linearly constrained DC (LCDC)-ALM and composite LCDC-ALM, targeting on different structures of the DC objective function. We show that both algorithms find an ϵ-approximate stationary solution of the original DC program in [Formula: see text] iterations. Comparing to existing methods designed for linearly constrained weakly convex minimization, the proposed ALM-based algorithms can be applied to a broader class of problems, where the objective contains a nonsmooth concave component. Finally, numerical experiments are presented to demonstrate the performance of the proposed algorithms. Funding: This work was partially supported by the NSF [Grant ECCS1751747]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/ijoo.2022.0087 .","PeriodicalId":73382,"journal":{"name":"INFORMS journal on optimization","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42942001","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: 8

Chvátal Rank in Binary Polynomial Optimization 二元多项式优化中的Chvátal秩

INFORMS journal on optimization Pub Date : 2021-03-26 DOI: 10.1287/IJOO.2019.0049

Alberto Del Pia, S. Di Gregorio

{"title":"Chvátal Rank in Binary Polynomial Optimization","authors":"Alberto Del Pia, S. Di Gregorio","doi":"10.1287/IJOO.2019.0049","DOIUrl":"https://doi.org/10.1287/IJOO.2019.0049","url":null,"abstract":"Recently, several classes of cutting planes have been introduced for binary polynomial optimization. In this paper, we present the first results connecting the combinatorial structure of these inequalities with their Chvátal rank. We determine the Chvátal rank of all known cutting planes and show that almost all of them have Chvátal rank 1. We observe that these inequalities have an associated hypergraph that is β-acyclic. Our second goal is to derive deeper cutting planes; to do so, we consider hypergraphs that admit β-cycles. We introduce a novel class of valid inequalities arising from odd β-cycles, that generally have Chvátal rank 2. These inequalities allow us to obtain the first characterization of the multilinear polytope for hypergraphs that contain β-cycles. Namely, we show that the multilinear polytope for cycle hypergraphs is given by the standard linearization inequalities, flower inequalities, and odd β-cycle inequalities. We also prove that odd β-cycle inequalities can be separated in linear time when the hypergraph is a cycle hypergraph. This shows that instances represented by cycle hypergraphs can be solved in polynomial time. Last, to test the strength of odd β-cycle inequalities, we perform numerical experiments that imply that they close a significant percentage of the integrality gap.","PeriodicalId":73382,"journal":{"name":"INFORMS journal on optimization","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48197054","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: 15

Editorial Board 编辑委员会

INFORMS journal on optimization Pub Date : 2021-01-01 DOI: 10.1287/ijoo.2021.eb.v3n1

引用次数: 0

Quasi-Stochastic Electricity Markets 准随机电力市场

INFORMS journal on optimization Pub Date : 2021-01-01 DOI: 10.1287/ijoo.2021.0051

J. Mays

引用次数: 16

Editorial Board 编辑委员会

INFORMS journal on optimization Pub Date : 2021-01-01 DOI: 10.1287/ijoo.2021.eb.v3n2

引用次数: 0

Integer Programming for Learning Directed Acyclic Graphs from Continuous Data. 从连续数据中学习有向无环图的整数编程。

INFORMS journal on optimization Pub Date : 2021-01-01 Epub Date: 2020-11-03 DOI: 10.1287/ijoo.2019.0040

Hasan Manzour, Simge Küçükyavuz, Hao-Hsiang Wu, Ali Shojaie

{"title":"Integer Programming for Learning Directed Acyclic Graphs from Continuous Data.","authors":"Hasan Manzour, Simge Küçükyavuz, Hao-Hsiang Wu, Ali Shojaie","doi":"10.1287/ijoo.2019.0040","DOIUrl":"10.1287/ijoo.2019.0040","url":null,"abstract":"<p><p>Learning directed acyclic graphs (DAGs) from data is a challenging task both in theory and in practice, because the number of possible DAGs scales superexponentially with the number of nodes. In this paper, we study the problem of learning an optimal DAG from continuous observational data. We cast this problem in the form of a mathematical programming model that can naturally incorporate a superstructure to reduce the set of possible candidate DAGs. We use a negative log-likelihood score function with both <math> <mrow><msub><mi>ℓ</mi> <mn>0</mn></msub> </mrow> </math> and <math> <mrow><msub><mi>ℓ</mi> <mn>1</mn></msub> </mrow> </math> penalties and propose a new mixed-integer quadratic program, referred to as a layered network (LN) formulation. The LN formulation is a compact model that enjoys as tight an optimal continuous relaxation value as the stronger but larger formulations under a mild condition. Computational results indicate that the proposed formulation outperforms existing mathematical formulations and scales better than available algorithms that can solve the same problem with only <math> <mrow><msub><mi>ℓ</mi> <mn>1</mn></msub> </mrow> </math> regularization. In particular, the LN formulation clearly outperforms existing methods in terms of computational time needed to find an optimal DAG in the presence of a sparse superstructure.</p>","PeriodicalId":73382,"journal":{"name":"INFORMS journal on optimization","volume":"3 1","pages":"46-73"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10088505/pdf/nihms-1885648.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9314757","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

An Algorithm for the Separation-Preserving Transition of Clusterings 一种保持分离的聚类转移算法

INFORMS journal on optimization Pub Date : 2020-12-10 DOI: 10.1287/ijoo.2022.0074

S. Borgwardt, Felix Happach, Stetson Zirkelbach

{"title":"An Algorithm for the Separation-Preserving Transition of Clusterings","authors":"S. Borgwardt, Felix Happach, Stetson Zirkelbach","doi":"10.1287/ijoo.2022.0074","DOIUrl":"https://doi.org/10.1287/ijoo.2022.0074","url":null,"abstract":"The separability of clusters is one of the most desired properties in clustering. There is a wide range of settings in which different clusterings of the same data set appear. We are interested in applications for which there is a need for an explicit, gradual transition of one separable clustering into another one. This transition should be a sequence of simple, natural steps that upholds separability of the clusters throughout. We design an algorithm for such a transition. We exploit the intimate connection of separability and linear programming over bounded-shape partition and transportation polytopes: separable clusterings lie on the boundary of partition polytopes and form a subset of the vertices of the corresponding transportation polytopes, and circuits of both polytopes are readily interpreted as sequential or cyclical exchanges of items between clusters. This allows for a natural approach to achieve the desired transition through a combination of two walks: an edge walk between two so-called radial clusterings in a transportation polytope, computed through an adaptation of classical tools of sensitivity analysis and parametric programming, and a walk from a separable clustering to a corresponding radial clustering, computed through a tailored, iterative routine updating cluster sizes and reoptimizing the cluster assignment of items.","PeriodicalId":73382,"journal":{"name":"INFORMS journal on optimization","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44211183","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

Editorial Board 编辑委员会

INFORMS journal on optimization Pub Date : 2020-10-01 DOI: 10.1287/ijoo.2020.eb.v2n4

引用次数: 0