{"title":"Strategic inattention of multi-product firms with free entry","authors":"Lijun Pan","doi":"10.1016/j.orl.2024.107068","DOIUrl":"https://doi.org/10.1016/j.orl.2024.107068","url":null,"abstract":"<div><p>This paper considers the strategic (in)attention of multi-product firms with endogenous product range choice and introduces free entry prior to firms' strategic choices on attention or inattention. We find that within-firm cannibalization of multi-product firms plays a key role in determining firms' strategic behavior. Furthermore, with free entry, we identify a single threshold that determines whether all the entrants are attentive or inattentive, and hence the market structure is unique almost everywhere.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139487271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal data pooling for shared learning in maintenance operations","authors":"Collin Drent, Melvin Drent, Geert-Jan van Houtum","doi":"10.1016/j.orl.2023.11.009","DOIUrl":"https://doi.org/10.1016/j.orl.2023.11.009","url":null,"abstract":"<div><p>We study optimal data pooling for shared learning in two common maintenance operations: condition-based maintenance and spare parts management. We consider systems subject to Poisson input – the degradation or demand process – that are coupled through an unknown rate. Decision problems for these systems are high-dimensional Markov decision processes (MDPs) and are thus notoriously difficult to solve. We present a decomposition result that reduces such an MDP to two-dimensional MDPs, enabling structural analyses and computations. Leveraging this decomposition, we (i) show that pooling data can lead to significant cost reductions compared to not pooling, and (ii) prove that the optimal policy for the condition-based maintenance problem is a control limit policy, while for the spare parts management problem, it is an order-up-to level policy, both dependent on the pooled data.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167637723001967/pdfft?md5=5d7da7aad5e8ffbfdd27776247120e5f&pid=1-s2.0-S0167637723001967-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139108726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Diffusion approximation of a special bandwidth sharing model via infinitesimal generators with a lifting-projection method","authors":"Bowen Xie , Yijin Gao","doi":"10.1016/j.orl.2023.107063","DOIUrl":"10.1016/j.orl.2023.107063","url":null,"abstract":"<div><p>We consider a proposed unsolved conjecture of a special bandwidth-sharing model integrating streamings and file transfers as initiated in Kumar and Massoulié (2007). Using the infinitesimal generator<span> approach, we demonstrate its diffusion approximation with a special time-scale separation parameter. To this end, we introduce a lifting-projection method, and exhibit a novel function to show the generator of a joint process converges to that of a univariate limiting file-transfer process, where the streaming flows are averaged out in heavy traffic.</span></p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139069710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A quadratic-order problem kernel for the traveling salesman problem parameterized by the vertex cover number","authors":"René van Bevern , Daniel A. Skachkov","doi":"10.1016/j.orl.2024.107065","DOIUrl":"10.1016/j.orl.2024.107065","url":null,"abstract":"<div><p><span>The NP-hard graphical traveling salesman problem (GTSP) is to find a closed walk of total minimum weight that visits each vertex in an undirected edge-weighted and not necessarily complete graph. We present a problem kernel with </span><span><math><msup><mrow><mi>τ</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>+</mo><mi>τ</mi></math></span> vertices for GTSP, where <em>τ</em> is the vertex cover number of the input graph. Any <em>α</em>-approximate solution for the problem kernel also gives an <em>α</em>-approximate solution for the original instance, for any <span><math><mi>α</mi><mo>≥</mo><mn>1</mn></math></span>.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139459457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On computing sparse generalized inverses","authors":"Gabriel Ponte , Marcia Fampa , Jon Lee , Luze Xu","doi":"10.1016/j.orl.2023.107058","DOIUrl":"10.1016/j.orl.2023.107058","url":null,"abstract":"<div><p>The M-P (Moore-Penrose) pseudoinverse is used in several linear-algebra applications. It is convenient to construct sparse block-structured matrices satisfying some relevant properties of the M-P pseudoinverse for specific applications. Aiming at row-sparse generalized inverses, we consider 2,1-norm minimization (and generalizations). We show that a 2,1-norm minimizing generalized inverse satisfies two additional M-P properties, including one needed for computing least-squares solutions. We present formulations related to finding row-sparse generalized inverses that can be solved very efficiently, which we verify numerically.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138684448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Partially egalitarian portfolio selection","authors":"Yiming Peng, Vadim Linetsky","doi":"10.1016/j.orl.2023.11.008","DOIUrl":"10.1016/j.orl.2023.11.008","url":null,"abstract":"<div><p>We propose a new portfolio optimization framework, partially egalitarian portfolio selection (PEPS). Inspired by the celebrated LASSO regression and its recent variant partially egalitarian LASSO (PELASSO) developed in <span>[1]</span> in the context of the forecast combinations problem in econometrics in <span>[1]</span>, we regularize the mean-variance portfolio optimization of Markowitz by adding two regularizing terms that essentially zero out portfolio weights of some of the assets in the portfolio and select and shrink portfolio weights of the remaining assets towards equal weights to hedge against parameter estimation risk. We solve our PEPS formulations by applying Gurobi 9.0 mixed integer optimization (MIO) solver that allow us to tackle large-scale portfolio problems. We test our PEPS portfolios against an array of classical portfolio optimization strategies on a number of datasets in the US equity markets. The PEPS portfolios exhibit the highest out-of-sample Sharpe ratios in all instances considered.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138566760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The complexity of geometric scaling","authors":"Antoine Deza , Sebastian Pokutta , Lionel Pournin","doi":"10.1016/j.orl.2023.11.010","DOIUrl":"10.1016/j.orl.2023.11.010","url":null,"abstract":"<div><p>Geometric scaling, introduced by Schulz and Weismantel in 2002, solves the integer optimization problem <span><math><mi>max</mi><mo></mo><mo>{</mo><mi>c</mi><mo>⋅</mo><mi>x</mi><mo>:</mo><mi>x</mi><mo>∈</mo><mi>P</mi><mo>∩</mo><msup><mrow><mi>Z</mi></mrow><mrow><mi>n</mi></mrow></msup><mo>}</mo></math></span> by means of primal augmentations, where <span><math><mi>P</mi><mo>⊂</mo><msup><mrow><mi>R</mi></mrow><mrow><mi>n</mi></mrow></msup></math></span><span> is a polytope. We restrict ourselves to the important case when </span><em>P</em> is a 0/1-polytope. Schulz and Weismantel showed that no more than <span><math><mi>O</mi><mo>(</mo><mi>n</mi><msub><mrow><mi>log</mi></mrow><mrow><mn>2</mn></mrow></msub><mo></mo><mi>n</mi><msub><mrow><mo>‖</mo><mi>c</mi><mo>‖</mo></mrow><mrow><mo>∞</mo></mrow></msub><mo>)</mo></math></span> calls to an augmentation oracle are required. This upper bound can be improved to <span><math><mi>O</mi><mo>(</mo><mi>n</mi><msub><mrow><mi>log</mi></mrow><mrow><mn>2</mn></mrow></msub><mo></mo><msub><mrow><mo>‖</mo><mi>c</mi><mo>‖</mo></mrow><mrow><mo>∞</mo></mrow></msub><mo>)</mo></math></span> using the early-stopping policy proposed in 2018 by Le Bodic, Pavelka, Pfetsch, and Pokutta. Considering both the maximum ratio augmentation variant of the method as well as its approximate version, we show that these upper bounds are essentially tight by maximizing over a <em>n</em>-dimensional simplex with vectors <em>c</em> such that <span><math><msub><mrow><mo>‖</mo><mi>c</mi><mo>‖</mo></mrow><mrow><mo>∞</mo></mrow></msub></math></span> is either <em>n</em> or <span><math><msup><mrow><mn>2</mn></mrow><mrow><mi>n</mi></mrow></msup></math></span>.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138493105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A note on clustering aggregation for binary clusterings","authors":"Jiehua Chen , Danny Hermelin , Manuel Sorge","doi":"10.1016/j.orl.2023.11.005","DOIUrl":"10.1016/j.orl.2023.11.005","url":null,"abstract":"<div><p>We consider the clustering aggregation problem in which we are given a set of clusterings and want to find an aggregated clustering which minimizes the sum of mismatches to the input clusterings. In the binary case (each clustering is a bipartition) this problem was known to be NP-hard under Turing reductions. We strengthen this result by providing a polynomial-time many-one reduction. Our result also implies that no <span><math><msup><mrow><mn>2</mn></mrow><mrow><mi>o</mi><mo>(</mo><mi>n</mi><mo>)</mo></mrow></msup><mo>⋅</mo><mo>|</mo><msup><mrow><mi>I</mi></mrow><mrow><mo>′</mo></mrow></msup><msup><mrow><mo>|</mo></mrow><mrow><mi>O</mi><mo>(</mo><mn>1</mn><mo>)</mo></mrow></msup></math></span>-time algorithm exists that solves any given clustering instance <span><math><msup><mrow><mi>I</mi></mrow><mrow><mo>′</mo></mrow></msup></math></span> with <em>n</em><span> elements, unless the Exponential Time Hypothesis fails. On the positive side, we show that the problem is fixed-parameter tractable with respect to the number of input clusterings.</span></p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138517286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jose Blanchet, Arun Jambulapati, Carson Kent, Aaron Sidford
{"title":"Towards optimal running timesfor optimal transport","authors":"Jose Blanchet, Arun Jambulapati, Carson Kent, Aaron Sidford","doi":"10.1016/j.orl.2023.11.007","DOIUrl":"10.1016/j.orl.2023.11.007","url":null,"abstract":"<div><p><span>We provide faster algorithms for approximating the optimal transport distance, e.g. earth mover's distance, between two discrete probability distributions on </span><em>n</em> elements. We present two algorithms which compute couplings between marginal distributions with an expected transportation cost that is within an additive <em>ϵ</em> of optimal in time <span><math><mover><mrow><mi>O</mi></mrow><mrow><mo>˜</mo></mrow></mover><mo>(</mo><msup><mrow><mi>n</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>/</mo><mi>ϵ</mi><mo>)</mo></math></span>; one algorithm is straightforward to parallelize and implementable in depth <span><math><mover><mrow><mi>O</mi></mrow><mrow><mo>˜</mo></mrow></mover><mo>(</mo><mn>1</mn><mo>/</mo><mi>ϵ</mi><mo>)</mo></math></span>. Further, we show that additional improvements on our results must be coupled with breakthroughs in algorithmic graph theory.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138517339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Saeed Marzban , Erick Delage , Jonathan Yu-Meng Li , Jeremie Desgagne-Bouchard , Carl Dussault
{"title":"WaveCorr: Deep reinforcement learning with permutation invariant convolutional policy networks for portfolio management","authors":"Saeed Marzban , Erick Delage , Jonathan Yu-Meng Li , Jeremie Desgagne-Bouchard , Carl Dussault","doi":"10.1016/j.orl.2023.10.011","DOIUrl":"10.1016/j.orl.2023.10.011","url":null,"abstract":"<div><p>We present a new portfolio policy convolutional neural network architecture, WaveCorr, for deep reinforcement learning applied to portfolio optimization. WaveCorr is the first to treat asset correlation while preserving “asset invariance property”, a new permutation invariance property that significantly increases the stability of performance in problems where input indexing is done arbitrarily. A general theory is also derived for verifying this property in other fields of application. Our experiments show that WaveCorr consistently outperforms other state-of-the-art convolutional architectures.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167637723001748/pdfft?md5=b7c5c893297ec90063fd55311e3c9b6e&pid=1-s2.0-S0167637723001748-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135455600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}