Journal of the Operations Research Society of Japan最新文献

IMPLEMENTING ARROW–DEBREU EQUILIBRIA IN APPROXIMATELY COMPLETE SECURITY MARKETS 在近似完整的证券市场中实现箭-德布雷乌均衡

Journal of the Operations Research Society of Japan Pub Date : 2024-01-31 DOI: 10.15807/jorsj.67.18

Koji Kusuda

引用次数: 0

A SUBGEOMETRIC CONVERGENCE FORMULA FOR TOTAL-VARIATION ERROR OF THE LEVEL-INCREMENT TRUNCATION APPROXIMATION OF M/G/1-TYPE MARKOV CHAINS m / g /1型马尔可夫链水平递增截断近似的总变差误差的次几何收敛公式

Journal of the Operations Research Society of Japan Pub Date : 2023-10-31 DOI: 10.15807/jorsj.66.243

Katsuhisa Ouchi, Hiroyuki Masuyama

引用次数: 1

A RIEMANNIAN-GEOMETRICAL APPROACH TO STRICTLY CONVEX QUADRATIC PROGRAMMING WITH CONVEXITY-PRESERVING METRIC PARAMETERIZATION 具有保凸度量参数化的严格凸二次规划的黎曼几何方法

Journal of the Operations Research Society of Japan Pub Date : 2023-10-31 DOI: 10.15807/jorsj.66.219

Toshihiro Wada, Toshiyuki Ohtsuka

{"title":"A RIEMANNIAN-GEOMETRICAL APPROACH TO STRICTLY CONVEX QUADRATIC PROGRAMMING WITH CONVEXITY-PRESERVING METRIC PARAMETERIZATION","authors":"Toshihiro Wada, Toshiyuki Ohtsuka","doi":"10.15807/jorsj.66.219","DOIUrl":"https://doi.org/10.15807/jorsj.66.219","url":null,"abstract":"In this study, we propose a new approach to strictly convex quadratic programming based on differential geometry. Broadly, our approach is an interior-point method. However, it can also be viewed as Newton's method on a Riemannian manifold on a set of interior points. In contrast to existing works on Newton's method on Riemannian manifolds, we introduce a parameterized metric and a retraction on the manifold, which are required to find a descent direction on the tangent space and update the solution on the manifold, respectively. The parameter of the metric is chosen at each iteration to preserve the local geodesic convexity of the objective function, while the retraction is designed to guarantee local convergence of the algorithm. The convergence rate is proven to be quadratic. Furthermore, we propose a modified algorithm emphasizing effective performance, which is numerically illustrated to be computationally as efficient as the primal-dual interior-point method, which has been widely used in practice. Our approach is also capable of warm start, which are preferable for model predictive control.","PeriodicalId":51107,"journal":{"name":"Journal of the Operations Research Society of Japan","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135928353","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: 0

A HYBRID ALGORITHM FOR THE ADWORDS PROBLEM ADWORDS问题的一种混合算法

Journal of the Operations Research Society of Japan Pub Date : 2023-07-31 DOI: 10.15807/jorsj.66.176

Iori Moriyama, S. Mizuno

引用次数: 0

MIXED-INTEGER DC PROGRAMMING BASED ALGORITHMS FOR THE CIRCULAR PACKING PROBLEM 基于混合整数dc规划的圆形布局问题算法

Journal of the Operations Research Society of Japan Pub Date : 2023-07-31 DOI: 10.15807/jorsj.66.153

Y. Ikebe, Satoru Masuda, Takayuki Okuno

引用次数: 0

KERNELIZATION ALGORITHMS FOR A GENERALIZATION OF THE COMPONENT ORDER CONNECTIVITY PROBLEM 广义分量序连通性问题的核化算法

Journal of the Operations Research Society of Japan Pub Date : 2023-04-30 DOI: 10.15807/jorsj.66.112

Masataka Shirahashi, Naoyuki Kamiyama

引用次数: 0

EX ANTE USER EQUILIBRIUM OF CAPACITATED NETWORKS 有容量网络的事前用户均衡

Journal of the Operations Research Society of Japan Pub Date : 2023-04-30 DOI: 10.15807/jorsj.66.130

Y. Masuda, Tomohiro Shigemasa

引用次数: 0

EFFECT OF ROAD PRICING ON TRAFFIC VOLUME AND TOLL REVENUE IN GRID NETWORK 路网道路收费对交通量和通行费收入的影响

Journal of the Operations Research Society of Japan Pub Date : 2023-04-30 DOI: 10.15807/jorsj.66.142

M. Miyagawa

引用次数: 0

STOCHASTIC INPUT MODELS FOR ONLINE COMPUTING 在线计算的随机输入模型

Journal of the Operations Research Society of Japan Pub Date : 2023-04-30 DOI: 10.15807/jorsj.66.95

Yasushi Kawase

{"title":"STOCHASTIC INPUT MODELS FOR ONLINE COMPUTING","authors":"Yasushi Kawase","doi":"10.15807/jorsj.66.95","DOIUrl":"https://doi.org/10.15807/jorsj.66.95","url":null,"abstract":"In this paper, we study twelve stochastic input models for online problems and reveal the differences between their competitive ratios for the models. The competitive ratio is defined as the worst ratio between the expected optimal value and the expected profit of the solution obtained by the online algorithm, where the input distribution is restricted according to the input model. Our purpose is to clarify the difference among the input models from the view of the competitive ratio. To handle a broad class of online problems, we use a framework called request-answer games, which were introduced by Ben-David et al. The stochastic input models fit into two categories: known distribution and unknown distribution. We consider six natural classes of distribution for each category: dependent distributions, deterministic input, independent distributions, identical independent distribution, random order of a deterministic input, and random order of independent distributions. Using each input model, we consider two fundamental online problems, which are variants of the secretary problem and the prophet inequality problem. We use these problems to observe the difference in the competitive ratios of each input model.","PeriodicalId":51107,"journal":{"name":"Journal of the Operations Research Society of Japan","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135668603","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: 0

APPROXIMATION ALGORITHM FOR STEINER TREE PROBLEM WITH NEIGHBOR-INDUCED COST 具有邻域诱导代价的steiner树问题的逼近算法

Journal of the Operations Research Society of Japan Pub Date : 2023-01-31 DOI: 10.15807/jorsj.66.18

Yusuke Kobayashi, Ryoga Mahara

引用次数: 0