@article{dai_fang_ling_nuttle_2008, title={Risk pooling strategy in a multi-echelon supply chain with price-sensitive demand}, volume={67}, ISSN={["1432-2994"]}, DOI={10.1007/s00186-007-0203-8}, number={3}, journal={MATHEMATICAL METHODS OF OPERATIONS RESEARCH}, author={Dai, Yue and Fang, Shu-Cherng and Ling, Xiaoli and Nuttle, Henry L. W.}, year={2008}, month={Jun}, pages={391–421} }
 @article{wang_fang_nuttle_2007, title={Fuzzy optimization and decision making (vol 2, pg 41, 2003)}, volume={6}, number={3}, journal={Fuzzy Optimization and Decision Making}, author={Wang, S. and Fang, S. C. and Nuttle, H. L. W.}, year={2007}, pages={297–297} }
 @article{wang_fang_nuttle_2007, title={Fuzzy optimization and decision making (vol 4, pg 331, 2005)}, volume={6}, number={3}, journal={Fuzzy Optimization and Decision Making}, author={Wang, S. and Fang, S. C. and Nuttle, H. L. W.}, year={2007}, pages={297–297} }
 @article{dai_chao_fang_nuttle_2006, title={Capacity allocation with traditional and Internet channels}, volume={53}, ISSN={["0894-069X"]}, DOI={10.1002/nav.20168}, abstractNote={Abstract}, number={8}, journal={NAVAL RESEARCH LOGISTICS}, author={Dai, Yue and Chao, Xiuli and Fang, Shu-Cherng and Nuttle, Henry L. W.}, year={2006}, month={Dec}, pages={772–787} }
 @article{dai_chao_fang_nuttle_2005, title={Game theoretic analysis of a distribution system with customer market search}, volume={135}, DOI={10.1007/s10479-005-6243-7}, number={1}, journal={Annals of Operations Research}, author={Dai, Y. and Chao, X. L. and Fang, Shu-Cherng and Nuttle, H. L. W.}, year={2005}, pages={223–238} }
 @article{dai_chao_fang_nuttle_2005, title={Pricing in revenue management for multiple firms competing for customers}, volume={98}, number={1}, journal={International Journal of Production Economics}, author={Dai, Y. and Chao, X. L. and Fang, S. C. and Nuttle, H. L. W.}, year={2005}, pages={16-} }
 @article{liao_fang_l.w. nuttle_2004, title={A neural network model with bounded-weights for pattern classification}, volume={31}, ISSN={0305-0548}, url={http://dx.doi.org/10.1016/s0305-0548(03)00097-2}, DOI={10.1016/S0305-0548(03)00097-2}, abstractNote={A new neural network model is proposed based on the concepts of multi-layer perceptrons, radial basis functions, and support vector machines (SVM). This neural network model is trained using the least squared error as the optimization criterion, with the magnitudes of the weights on the links being limited to a certain range. Like the SVM model, the weight specification problem is formulated as a convex quadratic programming problem. However, unlike the SVM model, it does not require that kernel functions satisfy Mercer's condition, and it can be readily extended to multi-class classification. Some experimental results are reported. Scopeandpurpose For the past decade, there has been increasing interest in solving nonlinear pattern classification problems. Among the various approaches, Multi-layer perceptrons, radial basis function networks and support vector machines have received most attention due to their tremendous success in real-world applications. Compared with the other two, The support vector machines approach is relatively new and often performs better in many applications. However, it also has some limitations, for example, kernel functions are required to satisfy Mercer's condition and it is not easily applicable for multi-class classification. In this paper, we propose a new neural network model which overcomes these limitations.}, number={9}, journal={Computers & Operations Research}, publisher={Elsevier BV}, author={Liao, Yi and Fang, Shu-Cherng and L.W. Nuttle, Henry}, year={2004}, month={Aug}, pages={1411–1426} }
 @article{fang_nuttle_wang_2004, title={Fuzzy formulation of auctions and optimal sequencing for multiple auctions}, volume={142}, ISSN={["1872-6801"]}, DOI={10.1016/S0165-0114(03)00127-1}, abstractNote={Current research on auctions is mainly based on the game theory. In the first part of this paper, we propose a fuzzy set based formulation of auctions. We define fuzzy sets to represent the seller and buyers’ valuations, bid possibilities and win possibilities. Analyzing the properties of these fuzzy sets, we study fuzzy versions of discriminating and nondiscriminating bidding strategies for each bidder in a single-object auction by using Bellman and Zadeh's concept of confluence of fuzzy decisions instead of the game theoretic Nash equilibrium. The monotonically decreasing membership function replaces of the corresponding distribution density function in Milgrom and Weber's auction theory. In the second part of the paper, we develop a soft computing approach to maximize the seller's revenue in multiple-object auctions through the use of object sequencing. The proposed sequencing approach is based on “fuzzy rule quantification”. Numerical experience shows the potential of the proposed approach for application in practical auctions.}, number={3}, journal={FUZZY SETS AND SYSTEMS}, author={Fang, SC and Nuttle, HWL and Wang, DW}, year={2004}, month={Mar}, pages={421–441} }
 @article{wu_fang_nuttle_2003, title={An  enhanced neural network learning using a self-tuning fuzzy neuron controller}, volume={14}, number={2}, journal={Journal of Intelligent & Fuzzy Systems}, author={Wu, P. and Fang, S. C. and Nuttle, H. L. W.}, year={2003}, pages={109–118} }
 @article{lertworasirikul_fang_joines_nuttle_2003, title={Fuzzy BCC model for data envelopment analysis}, volume={2}, ISSN={1568-4539}, url={http://dx.doi.org/10.1023/b:fodm.0000003953.39947.b4}, DOI={10.1023/b:fodm.0000003953.39947.b4}, number={4}, journal={Fuzzy Optimization and Decision Making}, publisher={Springer Science and Business Media LLC}, author={Lertworasirikul, S. and Fang, S-C. and Joines, J. A. and Nuttle, H. L.}, year={2003}, pages={337–358} }
 @article{lertworasirikul_fang_joines_nuttle_2003, title={Fuzzy data envelopment analysis (DEA): a possibility approach}, volume={139}, ISSN={["1872-6801"]}, DOI={10.1016/S0165-0114(02)00484-0}, abstractNote={Evaluating the performance of activities or organizations by traditional data envelopment analysis (DEA) models requires crisp input/output data. However, in real-world problems inputs and outputs are often imprecise. This paper develops DEA models using imprecise data represented by fuzzy sets (i.e., “fuzzy DEA” models). It is shown that fuzzy DEA models take the form of fuzzy linear programming which typically are solved with the aid of some methods to rank fuzzy sets. As an alternative, a possibility approach is introduced in which constraints are treated as fuzzy events. The approach transforms fuzzy DEA models into possibility DEA models by using possibility measures of fuzzy events (fuzzy constraints). We show that for the special case, in which fuzzy membership functions of fuzzy data are of trapezoidal types, possibility DEA models become linear programming models. A numerical experiment is used to illustrate the approach and compare the results with those obtained with alternative approaches.}, number={2}, journal={Fuzzy Sets and Systems}, publisher={Elsevier BV}, author={Lertworasirikul, S. and Fang, S. C. and Joines, J. A. and Nuttle, H. L. W.}, year={2003}, pages={379–394} }
 @article{liao_fang_nuttle_2003, title={Relaxed conditions for radial-basis function networks to be universal approximators}, volume={16}, ISSN={["0893-6080"]}, DOI={10.1016/S0893-6080(02)00227-7}, abstractNote={In this paper, we investigate the universal approximation property of Radial Basis Function (RBF) networks. We show that RBFs are not required to be integrable for the REF networks to be universal approximators. Instead, RBF networks can uniformly approximate any continuous function on a compact set provided that the radial basis activation function is continuous almost everywhere, locally essentially bounded, and not a polynomial. The approximation in L(p)(micro)(1 < or = p < infinity) space is also discussed. Some experimental results are reported to illustrate our findings.}, number={7}, journal={NEURAL NETWORKS}, author={Liao, Y and Fang, SC and Nuttle, HLW}, year={2003}, month={Sep}, pages={1019–1028} }
 @article{medaglia_fang_nuttle_wilson_2002, title={An efficient and flexible mechanism for constructing membership functions}, volume={139}, ISSN={["0377-2217"]}, DOI={10.1016/S0377-2217(01)00157-6}, abstractNote={This paper introduces a Bézier curve-based mechanism for constructing membership functions of convex normal fuzzy sets. The mechanism can fit any given data set with a minimum level of discrepancy. In the absence of data, the mechanism can be intuitively manipulated by the user to construct membership functions with the desired shape. Some numerical experiments are included to compare the performance of the proposed mechanism with conventional methods.}, number={1}, journal={EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}, author={Medaglia, AL and Fang, SC and Nuttle, HLW and Wilson, JR}, year={2002}, month={May}, pages={84–95} }
 @article{king_moon_nuttle_thoney_2002, title={Case Study Analysis of Inventory Stocking Policies to Support Replenishment: A Supply-chain Perspective}, volume={93}, ISSN={0040-5000 1754-2340}, url={http://dx.doi.org/10.1080/00405000208658356}, DOI={10.1080/00405000208658356}, abstractNote={Typically, in an attempt to optimize gross margin (revenue minus cost of goods), sourcing decisions for apparel products are based heavily on the lowest cost alternative. This is due to the assumption that the sourcing option does not affect the revenue side of the gross margin calculation, but it does impact the cost of goods. However, a fast, flexible supplier that can provide in-season replenishment can have a significant impact on revenue. Previous research has shown the benefit of including more than simple pre-season bottom line cost measures (e.g. King and Hunter, 1997; King and Maddalena, 1998; King et al., 1999; King, 2001). We present a case study of a manufacturer who hopes to capture the business of a major brand manufacturer who currently buys his product from a low cost, long lead time vendor. The study demonstrates the impact of in-season order replenishment, as well as the raw material inventory strategy, on the performance of a product line (program) for both the supplier and customer, as well as from a supply-chain perspective.}, number={3}, journal={Journal of the Textile Institute}, publisher={Informa UK Limited}, author={King, R. E. and Moon, W. K. and Nuttle, H. L.W and Thoney, K. A.}, year={2002}, month={Jan}, pages={25–35} }
 @article{wu_fang_nuttle_2002, title={Efficient neural network learning using second order information with fuzzy control}, volume={43}, ISSN={["0925-2312"]}, DOI={10.1016/S0925-2312(01)00336-8}, abstractNote={In this paper, we present a new learning method for back propagation training algorithms for neural networks. With the objective of reducing training time, we first introduce a curved search method with a fixed step size for determining weight adjustments. We then introduce a fuzzy controller for adjusting the step size to further reduce the training time and avoid the spikes in the training curve which sometimes occur with the fixed step size. Computational results indicate a strong potential for significant reduction in training time.}, number={2002 Mar}, journal={NEUROCOMPUTING}, author={Wu, PS and Fang, SC and Nuttle, HLW}, year={2002}, month={Mar}, pages={197–217} }
 @article{medaglia_fang_nuttle_2002, title={Fuzzy controlled simulation optimization}, volume={127}, ISSN={["1872-6801"]}, DOI={10.1016/S0165-0114(01)00153-1}, abstractNote={Simulation optimization deals with finding the values of input parameters of a complex simulated system which result in desired output. Traditional techniques may require an enormous amount of simulation runs to evaluate the system. To alleviate this problem, the proposed work provides the means of incorporating knowledge, expressed in natural language, that is often available among analysts and decision makers. Using convenient linguistic representations, the proposed mechanism can satisfy vaguely stated goals to a high degree (e.g. “high utilization” or “low inventory”). This mechanism is also able to generate an approximate Pareto optimal set in the presence of multiple goals. The optimization strategy used here depends on a fuzzy controller guided by a set of rules derived from statistical concepts, response surface models, and experts’ knowledge. To illustrate this approach we present computational experiments on the design of a flow line manufacturing system (in terms of a tandem of queues with blocking) with one and two goals. The actions derived from the controller, using approximate reasoning, are able to generate a high quality solution in only a few iterations. The results are compared extensively with those obtained with a genetic-based approach.}, number={1}, journal={FUZZY SETS AND SYSTEMS}, author={Medaglia, AL and Fang, SC and Nuttle, HLW}, year={2002}, month={Apr}, pages={65–84} }
 @article{nuttle_king_hunter_wilson_fang_2000, title={Simulation Modeling of the textile supply chain - Part 1: The textile-plant models}, volume={91}, ISSN={["0040-5000"]}, DOI={10.1080/00405000008659526}, abstractNote={In Part I of the series, we describe stochastic computer models that simulate operations in the spinning, knitting, weaving, dyeing and finishing, and cut/sew sectors of the textile industry. The models are scaled to represent a supply chain designed to feed a garment-manufacturing operation involving four or five plants, i.e. part of each plant's output is ‘dedicated’ while simultaneously providing yarns and fabrics to the industry at large. Each of the sector models is unique because of the very different types of processing technology employed. The models are linked by means of streams of fabric orders from the manufacturing plants that make a range of garment types requiring many different fabrics for Basic (year-round sales), Seasonal (two or three seasons per year), and Fashion (shelf lives of 8–12 weeks) goods in a broad range of colors. In addition to each plant's product ranges and order sizes and frequencies, particular attention is paid to the machine-scheduling algorithms, although the models are deliberately kept at a ‘high’ as opposed to a ‘shop-floor’ level. The purpose of this modeling is to allow senior management to answer broad questions about the plants' ability to operate in a Quick Response environment. The various model outputs reflect this, having a heavy emphasis on on-time shipments, back-order levels, and service levels. In Part II of the series, we shall present the QR-related operating results to date, a description of a master-scheduling procedure to orchestrate the operations of the supply chain, ideas on an improved scheduling method, and an account of the construction of neural-network decision surface models as a decision support tool. We also overview ongoing efforts in technology transfer and in using ‘fuzzy’ mathematics to model the vagueness and uncertainty inherent in the supply- chain decision-making environment. The research effort of which this is a part is ongoing. We present these results in the hope of encouraging others to help carry the investigations forward.}, number={1}, journal={JOURNAL OF THE TEXTILE INSTITUTE}, author={Nuttle, HLW and King, RE and Hunter, NA and Wilson, JR and Fang, SC}, year={2000}, pages={35–50} }
 @article{nuttle_king_fang_wilson_hunter_2000, title={Simulation Modeling of the textile supply chain - Part II: Results and research directions}, volume={91}, ISSN={["0040-5000"]}, DOI={10.1080/00405000008659527}, abstractNote={In Part I of this series we described a set of computer-simulation models of the various components of the apparel-supply complex. Here we summarize the results obtained by exercising the models, with the main emphasis placed on whether or not the upstream operations of spinning, fabric production, and dyeing and finishing were capable of meeting Quick Response (QR) requirements for response time and service levels. In carrying out this work, questions arose about the kind of information systems required to link the various entities in the supply chain, alternative scheduling procedures, the possibility of interactive management-information systems that would allow rapid responses to the concerns of senior managers, and user-friendly means for technology transfer. We have also begun to explore the use of fuzzy mathematics to model the uncertainty and vagueness inherent in most supply-chain decision-making. Work on these topics is discussed here in Part II.}, number={1}, journal={JOURNAL OF THE TEXTILE INSTITUTE}, author={Nuttle, HLW and King, RE and Fang, SC and Wilson, JR and Hunter, NA}, year={2000}, pages={51–64} }
 @inproceedings{fang_hung_nuttle_1999, title={A clustering-based approach to fuzzy systems identification}, number={1999 Aug.}, booktitle={Proceedings of the 8th International Fuzzy Systems Association World Congress, August 1999}, publisher={Piscataway, N.J.: IEEE}, author={Fang, S.-C. and Hung, T.-W. and Nuttle, H.}, year={1999} }
 @inproceedings{fang_chen_wu_huang_nuttle_1999, title={A fuzzy expert system for a wave soldering process}, number={1999 Aug.}, booktitle={Proceedings of the 8th International Fuzzy Systems Association World Congress. August 1999}, publisher={Piscataway, N.J.: IEEE}, author={Fang, S.-C. and Chen, S.-H. and Wu, P.-T. and Huang, M. and Nuttle, H.}, year={1999} }
 @inproceedings{fang_wang_chen_nuttle_1999, title={A new fuzzy due-date bargainer with soft computing}, number={1999 Aug.}, booktitle={Proceedings of the 8th International Fuzzy Systems Association World Congress. August 1999}, publisher={Piscataway, N.J.: IEEE}, author={Fang, S.-C. and Wang, D.-W. and Chen, S.-H. and Nuttle, H.}, year={1999} }
 @inproceedings{fang_hung_nuttle_1999, title={An easily implemented approach to fuzzy systems identification}, booktitle={18th International Conference of the North American Fuzzy Information Processing Society--NAFIPS: June 10-12, 1999, New York, N.Y., U.S.A.}, publisher={New York, N.Y.; Piscataway, N.J.: IEEE}, author={Fang, S.-C. and Hung, T.-W. and Nuttle, H.}, editor={R. N. Dave, T. SudkampEditor}, year={1999} }
 @inproceedings{fang_wu_nuttle_1999, title={Curved search based neural network learning using fuzzy control}, number={1999 Aug.}, booktitle={Proceedings of the 8th International Fuzzy Systems Association World Congress. August 1999}, publisher={Piscataway, N.J.: IEEE}, author={Fang, S.-C. and Wu, P.-T. and Nuttle, H.}, year={1999} }
 @inproceedings{fang_wang_nuttle_1999, title={Fuzzy rule quantification and its application in fuzzy due-date bargaining}, number={1999 Aug.}, booktitle={Proceedings of the 8th International Fuzzy Systems Association World Congress. August 1999}, publisher={Piscataway, N.J.: IEEE}, author={Fang, S.-C. and Wang, D.-W. and Nuttle, H.}, year={1999} }
 @article{wang_fang_nuttle_1999, title={Soft computing for multicustomer due-date bargaining}, volume={29}, ISSN={["1558-2442"]}, DOI={10.1109/5326.798770}, abstractNote={The due-date bargainer is a useful tool to support negotiation on due dates between a manufacturer and its customers. To improve the computational performance of an earlier version of the due-date bargainer, we present a new soft computing approach. It uses a genetic algorithm to find the best priority sequence of customer orders for resource allocation, and fuzzy logic operations to allocate the resources and determine the order completion times, following the priority sequence of orders. To extend the due-date bargainer to accommodate bargaining with several customers at the same time, we propose a method to distribute the total penalty using marginal penalties for the individual bargainers. A demonstration software package implementing the improved due-date bargainer has been developed. It is targeted at apparel manufacturing enterprises. Experiments using realistic resource data and randomly generated orders have achieved satisfactory results.}, number={4}, journal={IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS}, author={Wang, DW and Fang, SC and Nuttle, HLW}, year={1999}, month={Nov}, pages={566–575} }
 @inproceedings{fang_donovan_nuttle_wilson_1998, title={Multi-customer due-date bargaining with soft computing}, volume={2}, number={1998}, booktitle={Proceedings of the Fourth Joint Conference of Information Sciences. 1998}, author={Fang, S.-C. and Donovan, M. and Nuttle, H. and Wilson, J.}, year={1998}, pages={84–87} }
 @inproceedings{fang_chen_nuttle_king_1997, title={A fuzzy-control-based quick response reorder scheme for retailing of seasonal apparel}, volume={2}, booktitle={Joint Conference of Information Sciences: Semiotics, fuzzy logic, soft computing, computer vision, neural computing, genetic algorithm, pattern recognition, evolutionary computing}, publisher={Durham, NC: Duke University Machine Intelligence & Fuzzy Logic Laboratory}, author={Fang, S.-C. and Chen, T.-W. and Nuttle, H.L.W. and King, R. E.}, year={1997}, pages={300–303} }