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Optimizing (s, S) policies, for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第3期261卷 880-892页

作者： Qiu, Ruozhen Sun, Minghe Lim, Yun Fong Northeastern Univ Sch Business Adm Shenyang 110167 Liaoning Peoples R China Univ Texas San Antonio Dept Management Sci & Stat San Antonio TX 78249 USA Singapore Management Univ Lee Kong Chian Sch Business Singapore 178899 Singapore

This study considers a finite-horizon single-product periodic-review inventory management problem with demand distribution uncertainty. The problem is formulated as a dynamic program and the existence of an optimal (s, S) policy is proved. The corresponding dynamic robust counterpart models are then developed for the box and the ellipsoid uncertainty sets. These counterpart models are transformed into tractable linear and second-order cone programs, respectively. The effectiveness and practicality of the proposed robust optimization approaches are validated through a numerical study. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Inventory Periodic-review (s,S) policy Robust optimization Demand distribution uncertainty dynamic programing

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A rapid approximate dynamic programing based on constraint satisfaction for a series-parallel hybrid electric vehicle with a three-speed gearbox

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2023年第9期237卷 2329-2343页

作者： Sun, Qinpeng Wu, Wei Peng, Zengxiong Xing, Wei Wang, Haibin Beijing Inst Technol Sch Mech Engn 5 South Zhongguancun St Beijing 100081 Peoples R China Jing Jin Elect Technol Co Beijing Peoples R China

dynamic programing (DP) algorithm is frequently utilized in studies to solve the energy management schemes (EMS) of hybrid electric vehicles (HEVs). The results of this method are global optimal but computationally inefficient. This paper proposed a rapid approximate DP (RADP) algorithm to improve the time complexity to solve an off-line EMS for a series-parallel HEVs. The key step is to shorten search domain at each grid point of by calculating constraint variables and check constraints before implement Bellman equation. The results demonstrate the computing time has decreased to 1.6% of conventional DP with a slight increase of fuel consumption. And the control policy trajectories, SOC trajectories, and engine working point distribution of RADP are nearly identical to the DP in two driving missions for heavy vehicles.

关键词： Hybrid electric vehicle energy management scheme dynamic programing time complexity constraint satisfaction

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Dual dynamic programing with cut selection: Convergence proof and numerical experiments

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第1期258卷 47-57页

作者： Guigues, Vincent Fundacao Getulio Vargas Sch Appl Math 190 Praia Botafogo BR-22250900 Rio De Janeiro Brazil

We consider convex optimization problems formulated using dynamic programing equations. Such problems can be solved using the Dual dynamic programing algorithm combined with the Level 1 cut selection strategy or the Territory algorithm to select the most relevant Benders cuts. We propose a limited memory variant of Level 1 and show the convergence of DDP combined with the Territory algorithm, Level 1 or its variant for nonlinear optimization problems. In the special case of linear programs, we show convergence in a finite number of iterations. Numerical simulations illustrate the interest of our variant and show that it can be much quicker than a simplex algorithm on some large instances of portfolio selection and inventory problems. (C) 2016 Elsevier B.V. All rights reserved.

关键词： dynamic programing Nonlinear programing Decomposition algorithms Dual dynamic programing Pruning methods

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An integrated dominance analysis and dynamic programing approach for measuring predictor importance for customer satisfaction

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2019年第21期48卷 5290-5307页

作者： Brusco, Michael J. Cradit, J. Dennis Brudvig, Susan Florida State Univ Dept Business Analyt Informat Syst & Supply Chain Tallahassee FL 32306 USA Indiana Univ East Sch Business & Econ Richmond IN USA

Dominance analysis is a procedure for measuring the importance of predictors in multiple regression analysis. We show that dominance analysis can be enhanced using a dynamic programing approach for the rank-ordering of predictors. Using customer satisfaction data from a call center operation, we demonstrate how the integration of dominance analysis with dynamic programing can provide a better understanding of predictor importance. As a cautionary note, we recommend careful reflection on the relationship between predictor importance and variable subset selection. We observed that slight changes in the selected predictor subset can have an impact on the importance rankings produced by a dominance analysis.

关键词： Multiple regression predictor importance dominance analysis dynamic programing subset selection customer satisfaction

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Optimal starting control strategy of compound power-split system based on dynamic programing algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2023年第10-11期237卷 2580-2591页

作者： Wang, Bo Zhang, Zhendong Xu, Zishun Univ Shanghai Sci & Technol 580 Jungong Rd Shanghai 200093 Peoples R China

Hybrid electric vehicle has the advantages of internal combustion engine vehicle and pure electric vehicle. The mode transition from EV (electric vehicle) mode to HEV (hybrid electric vehicle) mode requires frequent engine starting. The engine ripple torque (ERT) at low speed will affect the stable operation of the output shaft and has a significant impact on ride comfort. In order to improve the effect of mode transition process, the distribution of motor torque is optimized. The engine ripple torque model is established by combining theoretical formula with experimental data. The dynamic torque of the compound power-split model is decoupled. The mode transition process from EV mode to HEV mode is analyzed. Aiming at power, ride comfort and economy, the optimal starting control strategy of engine is designed based on dynamic programing algorithm. The influence factors of starting process are studied. When the optimization grid of motor torque is 5, the best trade-off between optimization accuracy and calculation cost is obtained. The results show that, the best ride comfort is obtained by using the dynamic programing algorithm when the speed is 30 km center dot h(-1) and the load torque is -178 N center dot m. The starting effect is the best when the initial crank angle is 0 degrees while the transient response time is 0.84 s, compared with the initial crank angle of 90 degrees, the economy is improved by 21%.

关键词： Mode transition dynamic programing engine starting optimization compound power-split system hybrid vehicle

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EDISON-WMW: Exact dynamic programing Solution of the Wilcoxon–Mann–Whitney Test

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Genomics, Proteomics & Bioinformatics 2016年第1期14卷 55-61页

作者： Alexander Marx Christina Backes Eckart Meese Hans-Peter Lenhof Andreas Keller Chair for Clinical Bioinformatics Medical Faculty Saarland University Department of Human Genetics Saarland University University Hospital Chair for Bioinformatics Saarland University

In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon-Mann-Whitney （WMW） test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calcu- late the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we pre- sented different optimization strategies and developed a parallel solution. Using our program, the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molec- ular biomarkers for lung carcinoma and chronic obstructive pulmonary disease （COPD）. We foundthat approximated P values were generally higher than the exact solution provided by EDISON- WMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http：// ***/software/wtest/.

关键词： Wilcoxon-Mann-Whitneytest:Wilcoxon rank-sum test dynamic programing Exact permutation Parallel optimization

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Accuracy/Speed Trade-off Technique for dynamic programing Based Algorithms 5

Accuracy/Speed Trade-off Technique for Dynamic Programing Ba...

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5th International Conference on Electronic Devices, Systems and Applications (ICEDSA)

作者： Bonny, Talal Univ Sharjah Dept Elect & Comp Engn Sharjah U Arab Emirates

ISBN: (纸本)9781509053063

Although the dynamic programming algorithm is an optimization approach used to solve a complex problem fast, the time required to solve it is still not efficient and grows exponentially as a function of the size of the input. In this contribution, we improve the computation time of the dynamic programing based algorithms by proposing new acceleration technique which splits the compared sequences into segments and then applies the dynamic programming algorithm to each segment individually. The new technique is adjustable for either the alignment accuracy or the computation speed. The results show that our technique performs much faster than the conventional dynamic programming algorithm with a slight degradation in the performance and provides much accurate results than the heuristic algorithm based on number of segments.

关键词： dynamic programing database sequencing application computation time acceleration Needleman-Wunsch

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Concurrent Design of Assembly Plans and Supply Chain Configurations Using AND/OR Graphs and dynamic programing

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JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME 2016年第5期138卷 051011-051011页

作者： Kuang, Heng Hu, S. Jack Ko, Jeonghan Univ Michigan Mech Engn Ann Arbor MI 48109 USA Univ Michigan Ind & Operat Engn Ann Arbor MI 48109 USA Ajou Univ Dept Ind Engn Suwon 16499 South Korea

Making concurrent decisions on assembly plans and supply chain configurations (SCCs) is a desirable strategy in today's competitive global market. Such concurrent decisions help reduce decision iterations for shortened lead time and lower the total cost for manufacturers and their supply chains. However, there lacks deep understanding of the interaction between assembly plans and SCCs, as well as methodologies for integrating them. In this paper, we consider an assembly planning problem that simultaneously decomposes an assembly product to modules and assigns the modules to suppliers. The joint decision is formulated as an optimization problem of finding the assembly decomposition and the corresponding supply chain network with the lowest total supply chain cost. We develop a coordinated decision-making method by integrating assembly AND/OR graphs with supply chain cost information. A dynamic programing (DP) based algorithm is developed to efficiently solve the combined optimization problem. Case studies demonstrate that the proposed method can find optimal solutions for the integrated decision-making problem efficiently and provide a tool to plan assemblies from the perspective of the total supply chain cost in the early stages of product development.

关键词： assembly plan supply chain concurrent engineering AND/OR graph dynamic programing

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Weighting Optimization for Fuel Cell Hybrid Vehicles: Lifetime-Conscious Component Sizing and Energy Management

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APPLIED SCIENCES-BASEL 2025年第7期15卷 3586-3586页

作者： Xiao, Xuanyu Shu, Chen Dong, Huaiwei Tang, Yujun Feng, Jinfeng Yuan, Hao Bai, Shuzhan Zhu, Sipeng Li, Guoxiang Shandong Univ Sch Nucl Sci Energy & Power Engn Jinan 250061 Peoples R China Univ Bath Dept Mech Engn Bath BA2 7AY England Shandong Univ Shenzhen Res Inst Shenzhen 518057 Peoples R China

Featured Application We develop an integrated framework for component sizing and energy management in FCEVs;integrate economic and durability metrics using a weighting factor approach;analyze the impact of battery capacity and weighting factors on system performance;and evaluate the influence of battery pricing on fuel economy and system *** Fuel economy and system durability are critical yet interdependent performance metrics for fuel cell hybrid vehicles (FCHVs). This paper devises an integrated framework for optimizing component sizing and energy management in a fuel cell/battery hybrid passenger vehicle. A unified cost function is proposed, combining fuel economy and system durability through a weighting coefficient, based on a comprehensive model of the hydrogen consumption and degradation characteristics of fuel cells and batteries. Utilizing the dynamic programming (DP) algorithm, the total cost is optimized to derive the optimal weighting factors and component sizing, effectively addressing the multi-objective optimization problem and balancing efficiency and durability. Furthermore, the impact of power prices on the optimal parameters is carefully examined. The simulation results indicate that a battery capacity of 44 Ah and a fuel cell maximum power of 80 kW represent the optimal sizing configuration. A weighting factor of 0.5 achieves the minimum equivalent total cost by effectively balancing fuel economy and system durability for the light-duty fuel cell passenger vehicle. Additionally, the battery price affects the weighting factor, indicating that future reductions in power source costs will shift focus away from system durability to fuel economy in FCHV optimization. These findings provide recommendations for FCHV manufacturers to advance the application of fuel cells in passenger vehicles.

关键词： fuel cell hybrid vehicles component sizing energy management dynamic programing objective weighting

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Optimal selection of media vehicles using customer databases

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EXPERT SYSTEMS WITH APPLICATIONS 2012年第17期39卷 13035-13045页

作者： Malthouse, Edward C. Qiu, Dingxi Xu, Jie Northwestern Univ Dept Integrated Mkt Commun Evanston IL 60208 USA Univ Miami Coral Gables FL 33146 USA George Mason Univ Dept Syst Engn & Operat Res Fairfax VA 22030 USA

This paper investigates the problem where an organization must select among multiple media vehicles for a marketing campaign, and determine how many names from each vehicle to impress (the contact depth). The organization can estimate the return from contacting each prospective customer, and this return decreases as depth increases. Different vehicles have different marginal costs per impression, and may have minimum-spend requirements or activation costs to use the vehicle. Decisions are to be made to maximize profit subject to a constraint on the total amount spent. We proposed an optimization model and two computationally efficient methods that often lead to global optimal solutions under practical assumptions. The model is illustrated with two data sets. (c) 2012 Elsevier Ltd. All rights reserved.

关键词： Optimization Advertising Media vehicle Depth of purchase Revenue-to-cost ratio Internet marketing Mailing list dynamic programing

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