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A partial backordering approach to inventory control

PRODUCTION PLANNING & CONTROL 2001年第7期12卷 660-668页

作者： Zeng, AZ Worcester Polytech Inst Dept Management Worcester MA 01609 USA

We study the effects of using a partial backordering approach to controlling inventories under deterministic and stochastic demands, respectively. With a deterministic demand, our model is built with the objective of minimizing the total cost of ordering, holding, backordering and lost sales. The conditions for the partial backordering policy to be feasible are identified and a pair-wise comparison among the no-backordering, complete backordering, and partial backordering doctrines is conducted. In the stochastic case, we focus on a make-to-stock system with a Poisson demand and exponential production time, which allows us to establish a queuing model to examine the cost-effectiveness of using partial backorders. The conditions under which the partial backordering policy outperforms the complete backordering policy are identified.

关键词： inventory control non-linear programming optimizations stochastic process

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Optimal utilization of renewable energy-based IPPs for industrial load management

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RENEWABLE ENERGY 2009年第11期34卷 2455-2460页

作者： Babu, C. A. Ashok, S. Natl Inst Technol Dept Elect Engn CREC P O Calicut 673601 Kerala India

Share of power generation from renewable energy sources has been steadily increasing all over the world, mainly due to the concern about clean environment. Cost of renewable power generation has reduced considerably during the last two decades due to technological advancements and at present some of the renewable energy sources can generate power at costs comparable with that of fossil fuels. In this paper, application of renewable energy-based power generation is proposed, for load management. The formulation utilizes non-linear programming technique for minimizing the electricity cost and reducing the peak demand, by supplementing power by renewable energy sources, satisfying the system constraints. Case study of twenty-two large-scale industries showed that, significant reduction in peak demand (about 34%) and electricity cost (about 14%) can be achieved, by the optimal utilization of the renewable energy from independent power producers (IPPs). (C) 2009 Elsevier Ltd. All rights reserved

关键词： Wind Biomass Small hydro Peak demand non-linear programming

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An adaptive conic trust-region method for unconstrained optimization

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OPTIMIZATION METHODS & SOFTWARE 2005年第6期20卷 665-677页

作者： Han, QM Sun, WY Han, JY Sampaio, RJB Nanjing Normal Univ Sch Math & Comp Sci Nanjing 210097 Peoples R China Chinese Acad Sci Inst Appl Math Beijing 100080 Peoples R China Pontificia Univ Catolica Parana Grad Program Prod & Syst Engn BR-81611970 Curitiba Parana Brazil

It is well known that among the current methods for unconstrained optimization problems the quasi-Newton methods with global strategy may be the most efficient methods, which have local superlinear convergence. However, when the iterative point is far away from the solution of the problem, quasi-Newton method may proceed slowly for the general unconstrained optimization problems. In this article an adaptive conic trust-region method for unconstrained optimization is presented. Not only the gradient information but also the values of the objective function are used to construct the local model at the current iterative point. Moreover, we define a concept of super steepest descent direction and embed its information into the local model. The amount of computation in each iteration of this adaptive algorithm is the same as that of the standard quasi-Newton method with trust region. Some numerical results show that the modified method requires fewer iterations than the standard methods to reach the solution of the optimization problem. Global and local convergence of the method is also analyzed.

关键词： trust-region method conic model Quasi-Newton method non-linear programming self-adjust strategy

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A partial-postponement decision cost model

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2010年第1期201卷 34-44页

作者： Graman, Gregory A. Michigan Technol Univ Sch Business & Econ Houghton MI 49931 USA

A number of factors, including product proliferation and increased customer service-level requirements, have led many companies to consider adopting postponement as a supply chain strategy. Packaging postponement is the process of delaying packaging of a common item into a final product configuration until the customer order is received. For a given product, a portion of demand is known with a high level of certainty and would not benefit from postponement. The remaining portion of demand is known with little certainty and would benefit from delaying the differentiating stage of the operation until demand is known. We develop a single-period, two-product, order-up-to cost model to aid in setting the levels of finished-goods inventory and postponement capacity. Minimum-cost optimal solutions to inventory levels and capacity are obtained by solving the derived analytical expressions using a non-linear programming formulation. We examine the sensitivity of the model to different levels of the model parameters to generate managerial insights beyond those of previous work. We show that changing product value, packaging cost, cost of postponement, holding cost, fill rate, and demand correlation can decrease expected total cost and increase postponement capacity. (C) 2009 Elsevier B. V. All rights reserved.

关键词： Inventory non-linear programming Cost benefit analysis Mass customization Partial postponement

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Enhancing supply chain production-marketing planning with geometric multivariate demand function (a case study of textile industry)

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 140卷 106220-106220页

作者： Yaghin, R. Ghasemy Amirkabir Univ Technol Dept Text Engn Clothing Engn & Management Grp 424 Hafez Ave Tehran Iran

In this paper, a multi-period, multi-product, multi-site, multi-sles channel aggregate production planning problem including ordering preferences is presented in an integrated two-echelon supply chain to avoid the suboptimality caused by separate, sequential decisions of production and the marketing/retailing chain. Each customer demand class is affected by price, marketing expenditures and product quality involving customer willingness-to-pay. In addition, the immigration of customers between submarkets (i.e. cannibalization) is considered in the market-segmented environment due to imperfect segmentation. This research develops a geometric programming model to formulate the issue of joint price differentiation and multi-site aggregate production planning decisions by maximizing the total profit of the supply chain. To tackle the model and obtain solutions, we tailor an efficient analytical solution procedure to convert the original highly non-linear programming model into a convex programming equivalent. Finally, a numerical study of garment supply chain is presented to demonstrate the performance of the model and solution approaches. The research findings indicate a positive relationship between the scaling constant of price-dependent demand and the total profit rate. Moreover, as price gaps grow, the utility of price differentiation is decreased.

关键词： Multi-site production planning Integrated production-marketing Price differentiation Geometric programming non-linear programming

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Inductive linearization for binary quadratic programs with linear constraints: a computational study

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4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH 2024年第1期22卷 47-87页

作者： Mallach, Sven Univ Bonn High Performance Comp & Analyt Lab Friedrich-Hirzebruch-Allee 8 D-53115 Bonn Germany

The computational utility of inductive linearizations for binary quadratic programs when combined with a mixed-integer programming solver is investigated for several combinatorial optimization problems and established... 详细信息

关键词： non-linear programming Binary quadratic programming Mixed-integer programming linearization

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Product line selection and pricing under a share-of-surplus choice model

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2003年第3期150卷 653-671页

作者： Kraus, UG Yano, CA Univ Calif Berkeley IEOR Dept Berkeley CA 94720 USA Univ Calif Berkeley Haas Sch Business Berkeley CA 94720 USA

Product line selection and pricing decisions are critical to the profitability of many firms, particularly in today's competitive business environment in which providers of goods and services are offering a broad array of products to satisfy customer needs. We address the problem of selecting a set of products to offer and their prices when customers select among the offered products according to a share-of-surplus choice model. A customer's surplus is defined as the difference between his utility (willingness to pay) and the price of the product. Under the share-of-surplus model, the fraction of a customer segment that selects a product is defined as the ratio of the segment's surplus from this particular product to the segment's total surplus across all offered products with positive surplus for that segment. We develop a heuristic procedure for this non-concave, mixed-integer optimization problem. The procedure utilizes simulated annealing to handle the binary product selection variables, and a steepest-ascent-style procedure that relies on certain structural properties of the objective function to handle the non-concave, continuous portion of the problem involving the prices. We also develop a variant of our procedure to handle uncertainty in customer utilities. In computational studies, our basic procedures perform extremely well, producing solutions whose objective values are within about 5% of those obtained via enumerative methods. Our procedure to handle uncertain utilities also performs well, producing solutions with expected profit values that are roughly 10% higher than the corresponding expected profits from solutions obtained under the assumption of deterministic utilities. (C) 2002 Elsevier B.V. All rights reserved.

关键词： marketing pricing combinatorial optimization non-linear programming simulated annealing

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An optimization model for a monopolistic firm serving an environmentally conscious market: Use of chemical reaction optimization algorithm

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2015年 164卷 409-420页

作者： Choudhary, Alok Suman, Ravi Dixit, Vijaya Tiwari, M. K. Fernandes, Kiran Jude Chang, Pei-Chann Univ Loughborough Sch Business & Econ Loughborough LE11 3TU Leics England Indian Inst Technol Dept Ind & Syst Engn Kharagpur 721302 W Bengal India Natl Inst Ind Engn Bombay 400087 Maharashtra India Univ Durham Sch Business Durham England Yuan Ze Univ Dept Informat Management Taoyuan Taiwan

This work considers a monopolist firm which faces the following twin challenges of serving an environmentally sensitive market. The first challenge is the demand's elasticity to emissions and price. To entice its emission conscious customers and generate higher demand, the firm incrementally invests in cleaner production technologies. It also adopts a voluntary limit on its emissions from transportation. However, such investments and penalty lead to the second challenge of reduced net profit. To address above trade-off, a non-linear programming (NLP) model with a maximization quadratic profit function has been formulated. Recently developed, Chemical Reaction Optimization algorithm, with superior computational performance, has been adopted to solve the NLP. The output of the model provides near optimal monopolistic price, best attainable reduction in manufacturing emissions through proportional investment and makes a choice of suitable mode of transportation for each type of product offered by the firm. Three types of sensitivity analyses were performed by varying contextual parameters: customers' emission elasticity, penalty charged per unit emission and investment coefficient. The results, underpin the importance of investments in cleaner technologies and the need of financial aids for profit maximizing firms operating in cleaner markets. This work provides a decision making tool to determine the near optimal degree of each of the above dimension in multiple business fronts. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Emission elasticity Chemical reaction optimization non-linear programming Cleaner technologies

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Relationships of LA theorems for NRT structures by means of duality

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THEORETICAL AND APPLIED FRACTURE MECHANICS 2005年第3期44卷 261-274页

作者： Baratta, A Corbi, O Univ Naples Federico II Dip Sci Costruz I-80125 Naples Italy

The paper refers to previous works developed by the authors, dealing with the possibility of applying duality theorems to non-linear programs coming out from limit analysis (LA) of structures made by not resisting tension (NRT) or no-tension material. Under such perspective, after setting up the static or kinematic LA problem for NRT structures, the main task, for duality theorems to be applicable, is to demonstrate some convexity-related properties of the involved functions and domains. This feature, which is of basic importance for the whole procedure, is not trivial since all of the required conditions are to be accurately checked by analytical developments. Application of duality is finally demonstrated to give a complete and clear interpretation from a physical point of view about relationships relevant to LA approaches. (C) 2005 Elsevier Ltd. All rights reserved.

关键词： structural analysis NRT material duality non-linear programming limit analysis convexity

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Packing unit spheres into the smallest sphere using VNS and NLP

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COMPUTERS & OPERATIONS RESEARCH 2013年第2期40卷 603-615页

作者： M'Hallah, R. Alkandari, A. Mladenovic, N. Kuwait Univ Stat & Operat Res Dept Safat 13060 Kuwait Publ Author Appl Educ & Training Dept Appl Sci Safat 13092 Kuwait Brunel Univ Dept Math Sci Uxbridge UB8 3PH Middx England

This paper addresses the NP hard optimization problem of packing identical spheres of unit radii into the smallest sphere (PSS). It models PSS as a non-linear program (NIP) and approximately solves it using a hybrid heuristic which couples a variable neighborhood search (VNS) with a local search (LS). VNS serves as the diversification mechanism whereas LS acts as the intensification one. VNS investigates the neighborhood of a feasible local minimum u in search for the global minimum, where neighboring solutions are obtained by shaking one or more spheres of u and the size of the neighborhood is varied by changing the number of shaken spheres, the distance and the direction each sphere is moved. LS intensifies the search around a solution u by subjecting its neighbors to a sequential quadratic algorithm with non-monotone line search (as the NIP solver). The computational investigation highlights the role of LS and VNS in identifying (near) global optima, studies their sensitivity to initial solutions, and shows that the proposed hybrid heuristic provides more precise results than existing approaches. Most importantly, it provides computational evidence that the multiple-start strategy of non-linear programming solvers is not sufficient to solve PSS. Finally, it gives new upper bounds for 29 out of 48 benchmark instances of PSS. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Three-dimensional packing Unit-sphere packing non-linear programming Variable neighborhood search

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