{"title":"On Gaussian Markov processes and Polya processes","authors":"Kerry Fendick , Ward Whitt","doi":"10.1016/j.orl.2023.107062","DOIUrl":"10.1016/j.orl.2023.107062","url":null,"abstract":"<div><p><span><span><span>In previous work we characterized Gaussian Markov processes with </span>stationary increments and showed that they arise as </span>asymptotic approximations for stochastic </span>point processes with a random rate such as Polya processes, which can be useful to model over-dispersion and path-dependent behavior in service system arrival processes. Here we provide additional insight into these stochastic processes.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"52 ","pages":"Article 107062"},"PeriodicalIF":1.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139069653","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}
Emelin L. Buscaglia , Pablo A. Lotito , Lisandro A. Parente
{"title":"An inexact algorithm for stochastic variational inequalities","authors":"Emelin L. Buscaglia , Pablo A. Lotito , Lisandro A. Parente","doi":"10.1016/j.orl.2023.107064","DOIUrl":"10.1016/j.orl.2023.107064","url":null,"abstract":"<div><p><span>We present a new Progressive Hedging Algorithm to solve Stochastic Variational Inequalities in the formulation introduced by Rockafellar and Wets in 2017, allowing the generated </span>subproblems to be approximately solved with an implementable tolerance condition. Our scheme is based on Hybrid Inexact Proximal Point methods and generalizes the exact algorithm developed by Rockafellar and Sun in 2019, providing stronger convergence results. We also show some numerical experiments in two-stage Nash games.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"52 ","pages":"Article 107064"},"PeriodicalIF":1.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139069713","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 truthful constrained heterogeneous facility location with max-variant cost","authors":"Mohammad Lotfi , Alexandros A. Voudouris","doi":"10.1016/j.orl.2023.107060","DOIUrl":"10.1016/j.orl.2023.107060","url":null,"abstract":"<div><p>We consider a problem where agents have private positions on a line, and public approval preferences over two facilities, and their cost is the maximum distance from their approved facilities. The goal is to decide the facility locations to minimize the total and the max cost, while incentivizing the agents to be truthful. We design a strategyproof mechanism that is simultaneously 11- and 5-approximate for these two objective functions, thus improving the previously best-known bounds of <span><math><mn>2</mn><mi>n</mi><mo>+</mo><mn>1</mn></math></span> and 9.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"52 ","pages":"Article 107060"},"PeriodicalIF":1.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167637723002018/pdfft?md5=533c0ef6846afe12cb9dce906c7c37bb&pid=1-s2.0-S0167637723002018-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139026824","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":"Universally optimal staffing of Erlang-A queues facing uncertain arrival rates","authors":"Yaşar Levent Koçağa","doi":"10.1016/j.orl.2023.107061","DOIUrl":"10.1016/j.orl.2023.107061","url":null,"abstract":"<div><p><span>In many service systems, the staffing decisions must be made before the arrival rate is known with certainty. Thus, it is more appropriate to consider the arrival rate as a random variable at the time of the staffing decision. Motivated by this observation, we study the staffing problem in a service system modeled as an Erlang-A queue facing a </span><em>random</em> arrival rate. For linear staffing costs, linear waiting costs, and a cost per customer abandonment, we propose a policy that is based on modifying the well-known square-root safety staffing policy to explicitly account for the randomness in the arrival rate. Our primary contribution is to show that our proposed policy is “universally optimal”, i.e., <em>irrespective</em><span><span> of the magnitude of randomness in the arrival rate, the optimality gap between our proposed policy and the exact </span>optimal policy remains bounded as the system size grows large. This is important because earlier performance guarantees for Erlang-A queues either (1) are </span><em>not</em> universal and offer performance guarantees that depend on the magnitude of uncertainty in the arrival rate or (2) are universal but assume a <em>deterministic</em> arrival rate. The practical relevance of this provable robustness is that our proposed policy is a “one-size-fits-all” as it is guaranteed to perform well for <em>all</em> levels of arrival rate uncertainty.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"52 ","pages":"Article 107061"},"PeriodicalIF":1.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139070199","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":"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":"52 ","pages":"Article 107068"},"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":"52 ","pages":"Article 107056"},"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":"52 ","pages":"Article 107063"},"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":"52 ","pages":"Article 107065"},"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":"52 ","pages":"Article 107058"},"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":"52 ","pages":"Article 107055"},"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}