OPER: Continuous (Topic)最新文献

{"title":"Approximate Submodularity in Network Design Problems","authors":"Levi DeValve, S. Pekec, Y. Wei","doi":"10.2139/ssrn.3844987","DOIUrl":"https://doi.org/10.2139/ssrn.3844987","url":null,"abstract":"The paper “Approximate Submodularity in Network Design Problems” studies general network design problems where a firm strategically selects its network to better match supply and demand in the future. The paper observes that the arcs in network design problems are cover modular, i.e., approximately substitutes with each other, in the sense that local changes in the objective function can be used to bound global changes. The cover modularity is then applied to prove that a set of simple and intuitive heuristics achieve constant factor approximation guarantees in network design problems. Furthermore, the paper demonstrates cover modularity is also present in a general class of linear programming formulations.","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127258536","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}

{"title":"Price Optimization Under the Finite-Mixture Logit Model","authors":"Ruben van de Geer, Arnoud V. den Boer","doi":"10.2139/ssrn.3235432","DOIUrl":"https://doi.org/10.2139/ssrn.3235432","url":null,"abstract":"We consider price optimization under the finite-mixture logit model. This model assumes that customers belong to one of a number of customer segments, where each customer segment chooses according to a multinomial logit model with segment-specific parameters. We reformulate the corresponding price optimization problem and develop a novel characterization. Leveraging this new characterization, we construct an algorithm that obtains prices at which the revenue is guaranteed to be at least [Formula: see text] times the maximum attainable revenue for any prespecified [Formula: see text]. Existing global optimization methods require exponential time in the number of products to obtain such a result, which practically means that the prices of only a handful of products can be optimized. The running time of our algorithm, however, is exponential in the number of customer segments and only polynomial in the number of products. This is of great practical value, because in applications, the number of products can be very large, whereas it has been found in various contexts that a low number of segments is sufficient to capture customer heterogeneity appropriately. The results of our numerical study show that (i) ignoring customer segmentation can be detrimental for the obtained revenue, (ii) heuristics for optimization can get stuck in local optima, and (iii) our algorithm runs fast on a broad range of problem instances. This paper was accepted by Omar Besbes, revenue management and market analytics.","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124336204","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}

{"title":"Newsvendor Selling to Loss-Averse Consumers with Stochastic Reference Points","authors":"Opher Baron, Ming Hu, Sami Najafi-Asadolahi, Qu Qian","doi":"10.2139/ssrn.2329242","DOIUrl":"https://doi.org/10.2139/ssrn.2329242","url":null,"abstract":"We study a newsvendor who sells a perishable asset over repeated periods to consumers with a given consumption valuation for the product. The market size in each period is random, following a stationary distribution. Consumers are loss averse with stochastic reference points that represent their beliefs about possible price and product availability. Given the distribution of reference points, they choose purchase plans to maximize their expected total utility, including gain-loss utility, before visiting the store, and follow the plans in the store. In anticipation of consumers' purchase plans, in each period, before demand uncertainty resolves, the firm chooses an initial order quantity. After the uncertainty resolves, the firm chooses a contingent price depending on the demand realization, with the option of clearing inventory by charging a sale price, and otherwise, posting a full price. Over repeated periods, the interaction of the firm’s operational decisions about ordering and contingent pricing and...","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"08 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130715595","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}

{"title":"Portfolio Optimization for VAR, CVaR, Omega and Utility with General Return Distributions: A Monte Carlo Approach for Long-Only and Bounded Short Portfolios with Optional Robustness and a Simplified Approach to Covariance Matching","authors":"W. Shaw","doi":"10.2139/ssrn.1856476","DOIUrl":"https://doi.org/10.2139/ssrn.1856476","url":null,"abstract":"We develop the idea of using Monte Carlo sampling of random portfolios to solve portfolio investment problems. We explore the need for more general optimization tools, and consider the means by which constrained random portfolios may be generated. DeVroye's approach to sampling the interior of a simplex (a collection of non-negative random variables adding to unity) is already available for interior solutions of simple fully-invested long-only systems, and we extend this to treat, lower bound constraints, bounded short positions and to sample non-interior points by the method of Face-Edge-Vertex-biased sampling. A practical scheme for long-only and bounded short problems is developed and tested. Non-convex and disconnected regions can be treated by applying rejection for other constraints. The advantage of Monte Carlo methods is that they may be extended to risk functions that are more complicated functions of the return distribution, without explicit gradients, and that the underlying return distribution may be modeled parametrically or empirically based on general distributions. The optimization of expected utility, Omega, Sortino ratios may be handled in a similar manner to quadratic risk, VaR and CVaR, irrespective of whether a reduction to LP or QP form is available. Robustification is also possible, and a Monte Carlo approach allows the possibility of relaxing the general maxi-min approach to one of varying degrees of conservatism. Grid computing technology is an excellent platform for the development of such computations due to the intrinsically parallel nature of the computation. Good comparisons with established results in Mean-Variance and CVaR optimization are obtained, and we give some applications to Omega and expected Utility optimization. Extensions to deploy Sobol and Niederreiter quasi-random methods for random weights are also proposed. Extensions to the value functions of prospect theory are possible. The initial method proposed here is essentially an initial global search which produces a good feasible solution for any number of assets with any risk function and return distribution. This solution is close to optimal in lower dimensions. A by-product of these investigations is a simplified approach - the \"double-Cholesky method\" - to sampling certain multivariate distributions matching the covariance matrix as well as the mean vector.","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129828508","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}

{"title":"Optimization of a Stochastic Reverse Logistics Network with Refurbishment and Exchange Options","authors":"K. Lieckens, P. Colen, Marcella Lambrecht","doi":"10.2139/ssrn.1759210","DOIUrl":"https://doi.org/10.2139/ssrn.1759210","url":null,"abstract":"Remanufacturing activities are gaining momentum in the manufacturing industry. Therefore, the need for optimized networks becomes more pressing. In this paper we take a profit maximization approach to simultaneously determine the optimal network and the delivery strategy to support remanufacturing services offered to customers. In order to set up a network, investment decisions have to be made concerning the number, locations and types of remanufacturing facilities. Additionally, appropriate capacity and inventory levels have to be set in order to guarantee a given service level. These network decisions are influenced by the way the remanufacturing services are offered by the manufacturing firm. We consider two possible service delivery strategies: the service provider can either make a quick exchange of the used part by a refurbished one or re-install the original part after remanufacturing it. The model described in this paper is applied to optimize the network and service delivery strategy at a worldwide manufacturer of construction, mining and industrial equipment.","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130411098","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}

{"title":"Estimating Allocations for Value-at-Risk Portfolio Optimzation","authors":"A. Oulidi, Arthur Charpentier","doi":"10.2139/ssrn.1023911","DOIUrl":"https://doi.org/10.2139/ssrn.1023911","url":null,"abstract":"Value-at-Risk, despite being adopted as the standard risk measure in finance, but suffers severe objections from a practical point of vue, due to a lack of convexity, and since it does not reward diversification (which is an essential feature in portfolio optimization). Furthermore, it is also known as having poor behavior in risk estimation (which has been justified to impose the use of parametric models, but which induces then model errors). The aim of this paper is to chose in favour or against the use of VaR but to add some more information to this discussion, especially from the estimation point of view. Here we propose a simple method not only to estimate the optimal allocation based on a Value-at-Risk minimization constraint, but also to derive - empirical - confidence intervals based on the fact that the underlying distribution is unkown, and can be estimated based on past observations.","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125665878","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}

{"title":"Optimal Policies for a Capacitated Two-Echelon Inventory System","authors":"Rodney P. Parker, R. Kapuscinski","doi":"10.1287/opre.1040.0131","DOIUrl":"https://doi.org/10.1287/opre.1040.0131","url":null,"abstract":"This paper demonstrates optimal policies for capacitated serial multiechelon production/inventory systems. Extending the Clark and Scarf (1960) model to include installations with production capacity limits, we demonstrate that a modified echelon base-stock policy is optimal in a two-stage system when there is a smaller capacity at the downstream facility. This is shown by decomposing the dynamic programming value function into value functions dependent upon individual echelon stock variables. We show that the optimal structure holds for both stationary and nonstationary stochastic customer demand. Finite-horizon and infinite-horizon results are included under discounted-cost and average-cost criteria.","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128277053","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}

{"title":"A Model for Optimizing Electronic Toll Collection Systems","authors":"D. Levinson, Elva Chang","doi":"10.1016/S0191-2615(02)00021-8","DOIUrl":"https://doi.org/10.1016/S0191-2615(02)00021-8","url":null,"abstract":"","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127618816","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}

{"title":"A Survey of the Maximum Principles for Optimal Control Problems with State Constraints","authors":"R. Hartl, S. Sethi, R. Vickson","doi":"10.1137/1037043","DOIUrl":"https://doi.org/10.1137/1037043","url":null,"abstract":"This paper gives a survey of the various forms of Pontryagin's maximum principle for optimal control problems with state variable inequality constraints. The relations between the different sets of optimality conditions arising in these forms are shown. Furthermore, the application of these maximum principle conditions is demonstrated by solving some illustrative examples.","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122756495","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}

{"title":"Turnpike Sets and Their Analysis in Stochastic Production Planning Problems","authors":"S. Sethi, H. Soner, Qing Zhang, H. Jiang","doi":"10.1287/MOOR.17.4.932","DOIUrl":"https://doi.org/10.1287/MOOR.17.4.932","url":null,"abstract":"This paper considers optimal infinite horizon stochastic production planning problems with capacity and demand to be finite state Markov chains. The existence of the optimal feedback control is shown with the aid of viscosity solutions to the dynamic programming equations. Turnpike set concepts are introduced to characterize the optimal inventory levels. It is proved that the turnpike set is an attractor set for the optimal trajectories provided that the capacity is assumed to be fixed at a level exceeding the maximum possible demand. Conditions under which the optimal trajectories enter the convex closure of the set in finite time are given. The structure of turnpike sets is analyzed. Last but not least, it is shown that the turnpike sets exhibit a monotone property with respect to capacity and demand. It turns out that the monotonicity property helps in solving the optimal production problem numerically, and in some cases, analytically.","PeriodicalId":293182,"journal":{"name":"OPER: Continuous (Topic)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127049048","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}