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Establishing the optimal and efficient capacity re-allocation plans for enhancing the long-term competitiveness of a semiconductor product - a long-term trend viewpoint

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 2010年第B8期224卷 1295-1303页

作者： Chen, T. Feng Chia Univ Dept Ind Engn & Syst Management Taichung 40724 Taiwan

Yield is undoubtedly the most critical factor to the competitiveness of a product in a semiconductor manufacturing factory. Therefore, evaluating the competitiveness of a product with its yield is a reasonable idea. For this purpose, Chen's approach is extended in this study to evaluate the long-term competitiveness of a product based on its yield learning model from a new viewpoint - the trend in the mid-term competitiveness. Subsequently, to enhance the long-term competitiveness of a product, a non-linear programming approach is proposed to optimize the effects of capacity re-allocation. A practical example is used to demonstrate the proposed methodology. Experimental results show that with an additional capacity of 16 780 wafers per month, the long-term competitiveness of the product is maximized. Also, the most efficient way is to allocate 14 500 more wafers per month to the product. These results are helpful in making capacity re-allocation decisions.

关键词： semiconductor capacity re-allocation yield competitiveness non-linear programming

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New product introduction: goodwill, tinge and advertising cost

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MATHEMATICAL METHODS OF OPERATIONS RESEARCH 2002年第1期55卷 55-68页

作者： Buratto, A Viscolani, B Univ Padua Dipartimento Matemat Pura & Applicata I-35131 Padua Italy

The advertising activity has an important role in the introduction of a new product. We tackle the problem of determining the advertising plan for preparing the product introduction, having the objectives of maximizing the product image at the launch time, minimizing the campaign length and minimizing the total advertising expenditure, within a fixed time interval. After formulating the new product introduction optimal control problem, we study and solve two special cases of it, namely the minimum time and the advertising cost problems. From the former we derive the existence of an optimal solution of the original problem, whereas we obtain its structure from the latter. Finally we present two alternative formulations of the original problem in the non-linear programming framework and suggest using them to solve the bounded time problem.

关键词： marketing goodwill new product introduction optimal control non-linear programming

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A Simple Model of Capacity Contention During New Product Introductions

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IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING 2020年第2期33卷 240-251页

作者： Manda, Atchyuta Bharadwaj Uzsoy, Reha North Carolina State Univ Edward P Fitts Dept Ind & Syst Engn Raleigh NC 27695 USA

We consider the problem of determining an optimal release schedule for a production facility as it transitions from producing an older product to a newer one. We use simple queueing ideas to model the impact of the new product introduction on the throughput rate and cycle time of both products. We then incorporate the learning gained from accumulated experience in producing the new product to formulate a deterministic optimization model for release planning during product transitions. Since the model is nonlinear and non-convex we use a genetic algorithm to obtain near-optimal solutions. The structure of the optimal solution provides insights into the relationships between the different costs involved in the model. Computational experiments show that the release planning model produces high-quality solutions in reasonable CPU times, and reflects the behavior of the system realistically. The principal insight is that careful management of releases during product transitions has the potential to mitigate many of the adverse effects frequently observed in practice such as longer cycle times for both old and new products.

关键词： New product introduction learning effects non-linear programming genetic algorithms

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Energy-efficient spectrum sensing by optimal periodic scheduling in cognitive radio networks

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IET COMMUNICATIONS 2012年第6期6卷 676-684页

作者： Deng, R. He, S. Chen, J. Jia, J. Zhuang, W. Sun, Y. Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

Nowadays, with the dramatically increased penetration of wireless access, the conflict between spectrum scarcity and under-utilisation is becoming more and more aggravating. A promising technology to tackle such challenge is cognitive radio, of which spectrum sensing is one of the most important functionalities. In this study, the authors consider an essential problem of energy-efficient spectrum sensing in cognitive radio networks. Although most existing works of spectrum sensing mainly focus on determining an optimal sensing time to maximise the detection probability and/or to minimise the false alarm probability, our problem of how to schedule the power-constrained sensor is much more challenging, because of the trade-off among interests of the primary user, secondary user and sensor. The authors formulate it as a non-linear optimisation problem to maximise the sensor lifetime, with necessary constraints of quality and delay of spectrum sensing, and throughput for performance guarantee of primary and secondary users. Moreover, the authors incorporate the distribution information of channel occupancy/vacancy durations into the problem to yield a desirable solution. They propose a novel framework to obtain the optimal energy-efficient periodic scheduling by adopting both non-linear programming and linear programming. Extensive simulation results are provided to validate our theoretical analysis.

关键词： Radio access systems energy-efficient spectrum sensing non-linear programming false alarm probability radio access networks optimal periodic scheduling primary users power-constrained sensor radio spectrum management cognitive radio energy-efficient periodic scheduling cognitive radio networks non-linear optimisation problem wireless access scheduling secondary users

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Optimization of perturbed and constrained fuel-optimal impulsive rendezvous using a hybrid approach

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ENGINEERING OPTIMIZATION 2006年第8期38卷 959-973页

作者： Luo, Ya-Zhong Tang, Guo-Jin Wang, Zhong-Gui Li, Hai-Yang Natl Univ Def Technol Coll Aerosp & Mat Engn Changsha 410073 Peoples R China

The perturbed and constrained fuel-optimal impulsive rendezvous problem is formulated, developed, and solved. A non-linear programming model is established for the general perturbed fuel-optimal multiple-impulse time-fixed rendezvous with path constraints, and a hybrid approach is proposed as a global and efficient optimization tool. A floating-coded genetic algorithm is employed in this hybrid approach to locate an initial reference solution for sequential quadratic programming (SQP) using a simplified analytical propagator. Subsequently, SQP is used to locate the accurate solution using numerical integration of the high-fidelity trajectory dynamic equations. The hybrid approach is evaluated in three test cases: (i) Holman rendezvous and Lambert rendezvous, (ii) a three-impulse homing rendezvous with and without communication window constraints, and (iii) a four- and five-impulse non-coplanar multi-revolution rendezvous. The results show that the hybrid approach is effective and efficient in optimizing the perturbed and constrained fuel-optimal multiple-impulse rendezvous.

关键词： impulsive rendezvous fuel optimal perturbations non-linear programming genetic algorithm hybrid approach

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A generalized real-time obstacle avoidance method without the cspace calculation

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JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 2005年第6期20卷 774-787页

作者： Wang, YJ Cartmell, M Tao, QM Liu, H Chinese Acad Sci Lab Internet Software Technol Inst Software Beijing 100080 Peoples R China Univ Glasgow Ctr Syst & Control Glasgow G12 8QQ Lanark Scotland

An important concept proposed in the early stage of robot path planning field is the shrinking of a robot to a point and meanwhile the expanding of obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision-free path for a point robot among the Cspace obstacles. However, the research experiences have shown that the Cspace transformation is very hard when the following situations occur: 1) both the robot and obstacles are not polygons, and 2) the robot is allowed to rotate. This situation gets even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. For this reason, direct path planning approaches without the Cspace transformation is quite useful and expected. Motivated by the practical requirements of robot path planning, a generalized constrained optimization problem (GCOP) with not only logic AND but also logic OR relationships was proposed and a mathematical solution developed previously. This paper inherits the fundamental ideas of inequality and optimization techniques from the previous work, converts the obstacle avoidance problem into a semi-infinite constrained optimization problem with the help of the mathematical transformation, and proposes a direct path planning approach without Cspace calculation, which is quite different from traditional methods. To show its merits, simulation results in 3D space have been presented.

关键词： path planning obstacle avoidance autonomous underwater vehicle non-linear programming robotics semi-infinite constrained optimization

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Using dynamic optimization technique to study the operation of batch reactors

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CANADIAN JOURNAL OF CHEMICAL ENGINEERING 2007年第4期85卷 465-478页

作者： Sun, Daim-Yuang Lin, Pi-Min Lin, Shu-Ping Natl Chinyi Inst Technol Dept Chem & Mat Engn Taichung 11 Taiwan

How to apply the global optimization technique, simulated annealing, and to explore the operation of batch reactors is addressed in this study. Based on the operating purposes and the imposed constraints, the batch reactor operations are first formulated as two optimal control problems: the maximal yield (or conversion) problem and the minimal operating time problem. The problems are then converted into nonlinear programming problems by the concept of control vector parameterization. The converted problems are solved by the algorithm derived from simulated annealing to determine the optimal operating policy and the performance index. These results are useful in assessing design and operation of batch reactors. In this article, the CSTR model is used to demonstrate the convenience and robustness of the proposed algorithm. Two typical reaction models are used to discuss the operations based on the optimal solutions.

关键词： dynamic optimization batch reactor operations non-linear programming simulated annealing control vector parameterization

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Density based fuzzy c-means clustering of non-convex patterns

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2006年第3期173卷 717-728页

作者： Beliakov, Gleb King, Matthew Deakin Univ Sch Informat Technol Burwood 3125 Australia

We propose a new technique to perform unsupervised data classification (clustering) based on density induced metric and non-smooth optimization. Our goal is to automatically recognize multidimensional clusters of non-convex shape. We present a modification of the fuzzy c-means algorithm, which uses the data induced metric, defined with the help of Delaunay triangulation. We detail computation of the distances in such a metric using graph algorithms. To find optimal positions of cluster prototypes we employ the discrete gradient method of non-smooth optimization. The new clustering method is capable to identify non-convex overlapped d-dimensional clusters. (c) 2005 Elsevier B.V. All rights reserved.

关键词： data mining non-linear programming clustering fuzzy c-means non-smooth optimization

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Short-Term Hydrothermal Scheduling With Solar and Wind Farms Using Second-Order Cone Optimization With Chance-Box Constraints

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IEEE ACCESS 2021年 9卷 74095-74109页

作者： Camilo Castano, Juan Garces, Alejandro Fosso, Olav B. Univ Tecnol Pereira Dept Elect Power Engn Pereira 660003 Colombia Norwegian Univ Sci & Technol Dept Elect Power Engn N-7491 Trondheim Norway

Short-Term Hydrothermal Scheduling (STHS) is a classic problem in power system operation where the aim is to decide the dispatch of both thermal and hydroelectric units. This problem is complex due to its non-linear non-convex nature, and the requirements for fast solving for daily operation. Technologies such as wind and solar generation introduce stochastic behaviors, which have to be considered within the mathematical model. Although the problem is frequently solved by traditional and heuristic techniques, this paper proposes a new formulation based on convex approximations, and in particular, Second-Order Cone optimization, which addresses the nonlinear relation among water discharge, reservoir volume, and hydropower generation in a rigorous mathematical approach. Moreover, the impact of wind and solar generation on the power system is analyzed, modeling their stochastic behavior in a robust way by using chance-box constraints. Numerical results demonstrate that the Second-Order Cone approximation is precise and faster than techniques proposed recently and that the chance-box constraint approach guarantees a robust solution.

关键词： Hydroelectric power generation Stochastic processes programming Mathematical model Wind power generation Power systems Optimization Hydrothermal scheduling economic dispatch solar generation wind generation mathematical optimization non-linear programming chance-box constraints

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A stochastic AHP decision making methodology for imprecise preferences

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INFORMATION SCIENCES 2014年 270卷 192-203页

作者： Jalao, Eugene Rex Wu, Teresa Shunk, Dan Arizona State Univ Sch Comp Informat & Decis Syst Engn Tempe AZ 85281 USA Univ Philippines Dept Ind Engn & Operat Res Quezon City 1101 Philippines

Existing decision making methodologies like the Analytic Hierarchy Process (AHP) address imprecise pairwise comparisons by modeling crisp pairwise comparisons as fuzzy sets or a single type of probability distribution (e.g., uniform, triangular). However, one common issue faced by decision makers (DMs) is bounded rationality. That is, DMs have limited cognitive powers in specifying their preferences over multiple pairwise comparisons. This result to crisp as well as imprecise pairwise comparisons. Furthermore, given the ultimate goal of imprecise AHP is to make the decision, computing weights for the criteria and the alternatives from the imprecise preferences is a must. Hence, these various types of pairwise comparisons must be modeled using a single probability distribution for easy computation of the weights. In this research, a beta distribution is proposed to model the varying stochastic preferences of the DM. The method-of-moments methodology is used to fit the varying stochastic preferences of the DM into beta stochastic pairwise comparisons since it can represent a wide variety of probability distributions. Additionally, a non-linear programming model is then developed that calculates weights which maximize the preferences of the DM while maintaining a level of consistency. Comparison experiments are conducted using datasets collected from literature to validate the proposed methodology. Published by Elsevier Inc.

关键词： AHP Beta Distribution non-linear programming Imprecise Pairwise Comparisons Inconsistency

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