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A systematic decision-making approach for the optimal product-service system planning

EXPERT SYSTEMS WITH APPLICATIONS 2011年第9期38卷 11849-11858页

作者： Geng, Xiuli Chu, Xuening Xue, Deyi Zhang, Zaifang Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China Univ Calgary Dept Mech & Mfg Engn Calgary AB T2N 1N4 Canada

Product service system (PSS) planning has been attracting attentions of global manufacturers to change from providing only products to offering both products and their services as a whole. The PSS planning approach can maintain the functionality of products for customers throughout the whole product life-cycle. Identification of the product and service parameters in early design stages plays a critical role in PSS development. The PSS planning is usually started by the mapping from customer requirements (CRs) in the customer domain to engineering characteristics (ECs), including product-related ECs (P-ECs) and service-related ECs (S-ECs), in the functional domain. In this paper, a systematic decision-making approach for PSS planning is developed to determine the optimal fulfillment levels of ECs considering requirements of customers and manufacturers. The PSS planning is conducted through four phases. First, the initial weights of ECs considering customer needs are achieved based on fuzzy pairwise comparison. Second. the data envelopment analysis (DEA) approach is applied to obtain the final weights of ECs considering customer requirements as well as other requirements of the manufacturers. Third, the ECs are categorized into different Kano attribute classes using fuzzy Kano's questionnaire (FKQ) and fuzzy Kano's mode (FKM) for evaluation of the PSS. In the last phase, non-linear programming is carried out to maximize the fulfillment levels of ECs. A case study is carried out to demonstrate the effectiveness of the developed optimal PSS planning approach. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Product-service system (PSS) Engineering characteristics (EC) Fuzzy pairwise comparison Data envelopment analysis (DEA) Kano model non-linear programming

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A priority based assignment problem

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APPLIED MATHEMATICAL MODELLING 2016年第17-18期40卷 7784-7795页

作者： Kaur, Prabhjot Sharma, Anuj Verma, Vanita Dahiya, Kalpana Panjab Univ Univ Inst Engn & Technol Chandigarh 160014 India Panjab Univ Dept Math Chandigarh 160014 India Panjab Univ Dept Comp Sci & Applicat Chandigarh 160014 India

This paper discusses a priority based assignment problem related to an industrial project consisting of a total of n jobs. Depending upon its work breakdown structure, the execution of the project is carried out in two stages where the m primary jobs are performed first, in Stage-I whereas the (n - m) secondary jobs are performed later in Stage-II (as the secondary jobs cannot be performed until the primary jobs are finished). A number of manufacturing units exactly equal to n, each of them capable of performing all the n jobs involved in the project, are available. A tentative job-performance time taken by each of these manufacturing units for each of the n jobs is available. The purpose of the current study is to assign the jobs to the manufacturing units in such a way that the two stage execution of the project can be carried out in the minimum possible time. For this, a polynomial time iterative algorithm is proposed, which at each iteration, aims at selecting m manufacturing units to perform primary jobs corresponding to which, the remaining (n - m) manufacturing units perform the secondary jobs optimally and from this selection, a pair of times of Stage-I and Stage-II is obtained. The proposed algorithm is such that at each iteration, time of Stage-I decreases strictly and time of Stage-II increases. Out of the pairs so generated, the one with minimum sum of Stage-I and Stage-II times is considered as optimum and the corresponding assignment as the optimal assignment. A numerical illustration is given in the support of the theory. Also, the proposed algorithm is implemented and tested on a variety of test problems and the average run time for each problem is calculated. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Optimization non-linear programming Combinatorial analysis Allocation Assignment problem

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A fast decoupling capacitor budgeting algorithm for robust on-chip power delivery

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2004年第12期E87A卷 3273-3280页

作者： Fu, JJ Luo, ZY Hong, XL Cai, YC Tan, SXD Pan, Z Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China Univ Calif Riverside Dept Elect Engn Riverside CA 92521 USA

In this paper, we present an efficient method to budget onchip decoupling capacitors (decaps) to optimize power delivery networks in an area efficient way. Our algorithm is based on an efficient gradient-based non-linear programming method for searching the solution. Our contributions are an efficient gradient computation method (time-domain merged adjoint network method) and a novel equivalent circuit modeling technique to speed up the optimization process. Experimental results demonstrate that the algorithm is capable of efficiently optimizing very large scale P/G networks.

关键词： power delivery optimization decoupling capacitor non-linear programming

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Modelling, analysis and improvement of an integrated chance-constrained model for level of repair analysis and spare parts supply control

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2020年第10期58卷 3090-3109页

作者： Liu, Weimiao Liu, Kanglin Deng, Tianhu Tsinghua Univ Dept Ind Engn Beijing Peoples R China

In traditional practices, maintenance system and spare parts inventory control are usually considered in isolation, resulting in suboptimality. In a military system, the level of repair analysis (LORA) is often employed to help operate its repair networks. In this paper, we consider an integrated LORA and inventory control problem and formulate this problem as a mixed-integer nonlinear programming problem with chance constraints. Two second-order cone constraints are proposed to approximate the chance constraints. Furthermore, we propose an outer approximation (OA) algorithm based on the OA cuts. Extensive numerical results show that the OA algorithm significantly improves the computational efficiency under various types of components and network complexity. Next, we investigate the influence of service level and resource capacity, and propose the findings. Our results indicate that a higher service level leads to steeper costs, more resources, larger storage and heavier repair burdens at operating sites. Moreover, enhancements in resource capacity from the status quo lead to improvements in repairs and shrinkage in discards, bringing direct economic benefits. The insights extend to uncertain settings. It may be initially counterintuitive for many practitioners that demand uncertainty poses relatively subtle impacts.

关键词： Maintenance scheduling inventory control level of repair analysis non-linear programming

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A general non-linear optimization algorithm for lower bound limit analysis

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INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING 2003年第2期56卷 165-184页

作者： Krabbenhoft, K Damkilde, L Tech Univ Denmark Dept Civil Engn DK-2800 Lyngby Denmark

The non-linear programming problem associated with the discrete lower bound limit analysis problem is treated by means of an algorithm where the need to linearize the yield criteria is avoided. The algorithm is an interior point method and is completely general in the sense that no particular finite element discretization or yield criterion is required. As with interior point methods for linear programming the number of iterations is affected only little by the problem size. Some practical implementation issues are discussed with reference to the special structure of the common lower bound load optimization problem. and finally the efficiency and accuracy of the method is demonstrated by means of examples of plate and slab structures obeying different non-linear yield criteria. Copyright (C) 2002 John Wiley Sons. Ltd.

关键词： limit analysis finite element method lower bound method non-linear programming

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Random derivative-free algorithm for solving unconstrained or bound constrained continuously differentiable non-linear problems

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OPTIMIZATION METHODS & SOFTWARE 2015年第5期30卷 911-933页

作者： Jaberipour, Majid Khorram, Esmaile Karimi, Behrooz Amirkabir Univ Technol Dept Appl Math Fac Math & Comp Sci Tehran 15914 Iran Amirkabir Univ Technol Dept Ind Engn Tehran 15914 Iran

Derivative-free optimization is an area of long history which has so many applications in different fields. It has lately received considerable attention within the engineering community. This paper describes a random derivative-free algorithm for solving unconstrained or bound constrained continuously differentiable non-linear problems. This method is a combination of particle swarm and directional direct search algorithms. The key difference in direct search methods is in the way of generating positive bases. At first glance, a simple way of generating positive bases has been introduced for solving continuously differentiable problems. Then, it has been shown that using the particle swarm algorithm with a direct search algorithm can solve non-linear optimization problems efficiently. Some standard examples have been presented to demonstrate the ability and effectiveness of this approach.

关键词： particle swarm derivative-free unconstrained problems bound constrained problems non-linear programming

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Solving fractional optimal control problems with fixed or free final states by Haar wavelet collocation method

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IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION 2016年第2期33卷 543-561页

作者： Hosseinpour, Soleiman Nazemi, Alireza Univ Shahrood Sch Math Sci Dept Math POB ***-316 Shahrood Iran

A numerical method using Haar wavelets for solving fractional optimal control problems (FOCPs) is studied. The fractional derivative in these problems is in the Caputo sense. The operational matrix of fractional Riemann-Liouville integration and the direct collocation method are considered. The proposed technique is applied to transform the state and control variables into non-linear programming (NLP) parameters at collocation points. An NLP solver can then be used to solve FOCPs. Illustrative examples are included to demonstrate the validity and applicability of the proposed method.

关键词： fractional optimal control problems Caputo derivative rationalized Haar functions operational matrix non-linear programming

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Integrated decision-making in reverse logistics: an optimisation of interacting acquisition, grading and disposition processes

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2020年第19期58卷 5786-5805页

作者： Lechner, Gernot Reimann, Marc Karl Franzens Univ Graz Dept Prod & Operat Management Univ Str 15-E3 A-8010 Graz Austria

In view of global environmental and social challenges the transition towards a Circular Economy is considered as a crucial factor for sustainable development. Therefore, the replacement of traditional linear business models involving product discard at the end of product life with concepts focusing on re-use of resources is essential. Reverse Logistics and Closed-loop Supply Chains are seen to be key elements of such a transition. Motivated by findings from a case study of an independent reprocessing company, we address integrated decision-making in Reverse Logistics in this paper. We present a non-linear optimisation model with interrelated processes in terms of acquisition of used products, grading for determination of product quality and reprocessing disposition. The decisions to be made concern the effort spent for active acquisition of used products and the number of reprocessed goods;both decisions are influenced by heterogeneous condition of used products. The consideration of deterministic and stochastic demand facilitates the representation of a variety of business cases. For both demand types we provide analytical insights in the form of complete strategies consisting of different scenarios which allow optimal decision-making under variable conditions. Numerical examples complement insights into the model by conducting a sensitivity analysis of relevant model parameters.

关键词： reverse logistics decision support systems non-linear programming newsvendor integrated decision-making

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Convexification method for bilinear transmission expansion problem

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2014年第5期24卷 638-652页

作者： Cedeno, Enrique B. Arora, Sant Univ Minnesota Ind & Syst Engn Dept Minneapolis MN 55455 USA

This research presents a method for convexifying the non-linear constraints and the objective function for the Transmission Network Expansion Planning Problem (TNEP). The TNEP seeks to identify the best set of transmission capacity additions to meet a future electric power demand. The TNEP is a non-convex Mixed Integer non-linear programming problem for which a variety of primal solution methods have been designed. In this paper, the TNEP is formulated as a bilinear programming problem subject to bilinear constraints. This allows resolving the non-linearities through convexification of the non-linear objective function and the constraints for a relaxation of the TNEP in which integrality requirements are removed. The final solution for the original TNEP problem is obtained by using a branch and bound strategy. It was found by using a two-node test case that the convexification method presented in this paper in conjunction with a brand and bound strategy identifies the optimal solution. Successfully solving a small-scale test problem through convexification presents a promising scenario to solve larger scale problems. This primal-dual method allows identifying the duality gap which is a limitation of primal methods. Further multidisciplinary research is needed to extend the method presented here to larger cases and real life networks. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： bilinear programming non-linear programming convexification transmission planning

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Urban planning for low-income groups with developed optimization models

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ADVANCES IN ENGINEERING SOFTWARE 2003年第10期34卷 607-619页

作者： Awad, AR Aboul-Ela, MT Tishreen Univ Dept Environm Engn Latakia Syria Minya Univ Dept Civil Engn Minya Egypt

This article presents a methodology and new technique for residential land planning for low-income groups. Several unit design modules for the residential area are suggested and a cost optimization model for obtaining the optimum physical design of one module satisfying the geometric, density, and other constraints has been formulated as a non-linear programming problem. The solution came through a relatively simplified Focus Search and Monte-Carlo Simulation techniques. A second model for the optimal design of the dwelling-layout has been developed with an objective function of maximization of lot dimensions and satisfying some constraints, most important of which is the affordability for low-income groups. The optimum design, based on this model, came by using the relatively simple computer-based Focus Search technique. A practical application of the two models for Syria is illustrated by an example about obtaining a residential neighborhood from several planning modules combined together. A case study revealed how a planner, can achieve directly the desired feasible and optimal design solutions, depending on these new planning techniques. (C) 2003 Published by Elsevier Ltd.

关键词： optimization models land-use planning dwelling-layout system non-linear programming focus search method Monte-Carlo simulation

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