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Now showing items 17 - 32 of 43

  • On the Robust and Stable Flowshop Scheduling Under Stochastic and Dynamic Disruptions

    Liu, Feng   Wang, Shengbin   Hong, Yuan   Yue, Xiaohang  

    In this paper, we consider a permutation flowshop scheduling problem with the total flow time as the schedule performance measure. A proactive-reactive approach is designed to simultaneously deal with stochastic disruptions (e.g., machine breakdowns) and dynamic events (e.g., newly arriving jobs and delay in job availability). In the proactive stage, the stochastic machine breakdown is hedged against the construction of a robust and stable baseline schedule. This schedule is either optimized by incorporating uncertainty into two surrogate measures or obtained by simulation. Robustness is measured by the expected schedule performance, while stability is measured by the aggregation of dissatisfactions of manager, shopfloor operator, and customers using the prospect theory. In the reactive stage, we assume that the stochastic and dynamic disruptions concurrently occur. Unlike the simple right-shifting method, a more effective rescheduling approach is proposed to balance the realized schedule performance with stability. A common issue in these two stages is the conflict between objectives. Thus, we propose a hybridization strategy that successfully enhances the classic Non-dominated Sorting Genetic Algorithm (NSGA-II and the hybridized algorithm outperforms NSGA-II, multiobjective evolutionary algorithm based on decomposition, and multiobjective memetic algorithms designed for deterministic scheduling problems. Finally, extensive computational studies on the Taillard flowshop benchmark instances are conducted to illustrate the effectiveness of the proposed proactive-reactive approach and the algorithm hybridization strategy.
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  • Analysis of the Bullwhip Effect in a Multiproduct Setting with Interdependent Demands

    Raghunathan, Srinivasan   Tang, Christopher S.   Yue, Xiaohang  

    The bullwhip effect has been extensively studied primarily based on the analysis of various single-product models with a few exceptions. We extend the single-product analysis to the multiproduct setting of interdependent demand streams with auto-correlation and cross-product correlation, as well as contemporaneous correlation across forecasting errors. We find that interdependency between demand streams plays a critical role in determining the existence and magnitude of the bullwhip effect. Specifically, we consider two operating environments: (a) The firm orders product-specific materials so that the ordering decision is based on the product level; and (b) the firm orders generic materials so that the order decision is based on the category level. We show that, even with demand pooling, a firm operating at the category level can experience a larger bullwhip effect and a larger order variance under certain conditions that depend on the number of products in the category and the demand dependencies.
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  • An Effective Optimization Algorithm for Application Mapping in Network-on-Chip Designs

    Wang, Xinyu   Choi, Tsan-Ming   Yue, Xiaohang   Zhang, Mengji   Du, Wanyu  

    The application mapping problem is an NP-hard combinatorial optimization problem in network-on-chip (NoC) design. Applications of size (n > 30) cannot be solved optimally by an exact algorithm in reasonable time, and the evolutionary algorithms have drawn the attention of NoC researchers. In this paper, we propose a new effective optimization method based on the discrete particle swarm optimization framework, which includes the novel principles for representation, velocity computing, and position-updating of the particles. In our proposed method, particles are allowed to swing between elite and regular pools, and a simple local search procedure is applied on elite particles to exploit the promising solutions. Extensive computational studies using standard benchmark instances and task graphs for free (TGFF) random instances reveal that the proposed optimization algorithm is able to attain the best results, and thus competes very favorably with the previously proposed heuristic approaches. A stability analysis and the two-sided Wilcoxon rank sum tests are also presented to shed light on the robust behavior of the algorithm.
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  • Operations Sequencing in Flexible Production Lines With Bernoulli Machines

    Zhang, Liang   Yue, Xiaohang  

    In flexible manufacturing environments, the performance of a production system is often affected by the sequence of operations. While performance evaluation, improvement and lean design of production systems have been studied extensively, the joint effect of productivity and quality parameters on operations sequencing remains practically unexplored. Indeed, determining the optimal operation sequence has significant implications from both practical and theoretical perspectives. In this paper, in the framework of Bernoulli reliability and quality models, we develop effective indicators that are simple and easy to implement in practice to determine the optimal operation sequence that maximizes the system's production rate. Note to Practitioners-This paper shows how one can determine the optimal sequence in a two-machine-one-buffer serial line based on indicators, which are simple functions of the productivity and quality parameters of the machines and the capacity of the buffer. It demonstrates that the machine with higher efficiency and/or lower quality should be placed upstream to maximize the throughput. Finally, it shows that if the buffer is sufficiently large, then the machine with higher efficiency should always be placed upstream regardless of the quality performance of the machines.
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  • Optimal Remanufacturing Certification Contracts in the Electrical and Electronic Industry

    Liu, Huihui   Yue, Xiaohang   Ding, Hui   Leong, G. Keong  

    While remanufacturing is highly encouraged worldwide, some original equipment manufacturers (OEMs) in the electrical and electronics industry are still not willing to embrace remanufacturing, for fear of expensive investment or the cannibalization of existing products. Meanwhile, third-party remanufacturers' (TPRs) remanufactured products are developing quickly. Due to quality reasons, consumers usually have a higher preference for OEM-certified remanufactured products than uncertified ones. As such, remanufacturing certification has become a strategy that OEMs can use to benefit from product remanufacturing. Our paper focuses on the remanufacturing certification contract between an OEM and a TPR. Once certified, the TPR makes payments to the OEM. These payment terms will affect their enthusiasm for participating in remanufacturing certification. By establishing game models among an OEM, a certified TPR, and an uncertified TPR, our paper explores three certification contracts, namely, the lump-sum payment, profit-sharing payment, and piece-rate payment. We identify the conditions for the OEM and certified TPR to reach a win-win outcome. Our results show that when TPRs have a high profit margin and there is no significant difference in consumers' preferences between certified and non-certified remanufacturing channels, the profit-sharing payment contract yields the highest profit; otherwise, the piece-rate payment contract is best for the OEM.
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  • Evolutionary Strategies of Supply Chain Finance From the Perspective of a Return Policy

    Zhang, Baojian   Ye, Yang   Yue, Xiaohang  

    Return policy and supply chain finance are significant measures for banks and enterprises to improve the overall competitiveness of their supply chain. Supervision and guidance by banks are prerequisites to the smooth implementation of return policy and supply chain finance. This study analyzes the evolutionary stable strategy of three parties, namely, one bank, one supplier and one retailer, by establishing an asymmetric evolutionary game model. The model assumes that banks apply a reward and punishment policy for suppliers and retailers. Results show that regardless of the strategy the bank chooses, one party will always choose non-implementation of the return policy or non-adoption of the supply chain finance. From a short-term perspective, regardless of the strategy the bank chooses, suppliers and retailers will select the strategy of non-implementation and non-adoption, respectively. From the long-term perspective, suppliers and retailers will actively choose implementation and adoption whether or not there is bank supervision.
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  • A Stackelberg model of pricing of complementary goods under information asymmetry

    Mukhopadhyay, Samar K.   Yue, Xiaohang   Zhu, Xiaowei  

    We consider a duopoly market where two separate firms offer complementary goods in a leader-follower type move. Each firm has private forecast information about the uncertain market demand and decides whether to share it with the other firm. We show that information sharing would benefit the leader firm but hurt the follower firm as well as the total system if the follower firm shares information unconditionally. We then devise a "simple to implement" information sharing scheme under which both firms and the total system are better off. We also provide several interesting managerial insights and establish the robustness of the model in managing a supply chain through our analytical and simulation results. (C) 2009 Elsevier B.V. All rights reserved.
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  • Strategic inventory deployment for retail and e-tail stores

    Yao, Don-Qing   Yue, Xiaohang   Mukhopadhyay, Samar K.   Wang, Ziping  

    In this paper, we study a supply chain comprising one manufacturer and one retailer. Customers can make purchases either from the retailer or directly from the manufacturer via an e-tail channel. From the manufacturer's perspective of managing the two channels. we stud three different inventory strategies, namely centralized inventory strategy, a Stackelberg inventory strategy, and a strategy where the e-tail operation is outsourced to a third party lolgistics provider (3PL). For each strategy, we obtain the optimal inventory levels in retail and e-tail stores and the respective expected profits. We compare the performance of various strategies. Managerial insights are provided through analytical and numerical analyses to illustrate the applicability of different strategies. (c) 2008 Elsevier Ltd. All rights reserved.
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  • A newsvendor model with autocorrelated demand under a time-consistent dynamic CVaR measure

    Shi, Ye   Alwan, Layth C.   Tang, Christopher   Yue, Xiaohang  

    As a result of autocorrelation, static risk measures such as value at risk and Conditional Value at Risk (CVaR) are time inconsistent and can thus result in inconsistent decisions over time. In this article, we present a time-consistent dynamic CVaR measure and examine it in the context of a newsvendor problem with autocorrelated demand. Due to the concavity of our CVaR measure, the dynamic program formulation associated with our dynamic newsvendor problem is not immediately separable. However, by exploring certain properties of the dynamic CVaR measure and underlying profit function, our dynamic program can be transformed into a sequence of (single-period) risk-averse newsvendor problems that depend on the observed demand history. By examining the structure of the optimal order quantities, we find both intuitive and counterintuitive results. When demands are positively correlated, the optimal order quantity is monotonically increasing in the degree of risk aversion. However, when demands are negatively correlated and the underlying cost structure satisfies certain conditions, the optimal order quantity is no longer monotonically increasing in the degree of risk aversion. Instead, the optimal order quantity is a decreasing (increasing) function of the degree of risk aversion when it is below (above) a certain threshold. We also show that these results continue to hold when demands follow a general ARMA process, and when inventory carryover is considered.
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  • Does buy-back induce more fashion sub-sourcing? Contract property and performance analysis

    Niu, Baozhuang   Chen, Lei   Zhuo, Xiaopo   Yue, Xiaohang  

    In fashion industry, we observe that fashion brands like Zara and Gymboree rely on Li & Fung for their clothes manufacturing, but procure materials by themselves (referred to as direct-sourcing in this paper). In contrast, Calvin Klein and Timberland authorize Li & Fung to sub-source materials and manufacture clothes (referred to as sub-sourcing in this paper). Motivated by these observations, we consider a three-layer supply chain comprising of a material supplier, a procurement agent and a fashion brand, and analyze their preferences over two typical procurement structures: direct-sourcing and sub-sourcing. Under sub-sourcing, buy-back contracts, through which fashion brands return unsold products and thus shift overstock risk to procurement agents, are widely adopted in fashion industry. We identify demand enlargement effect and wholesale power effect of the buy-back contract under sub-sourcing. These two effects change the fashion brands' profit balance between direct-sourcing and sub-sourcing, and may induce the fashion brand to prefer sub-sourcing. We further examine the impact of demand uncertainty on the fashion brand's profits, and observe that sub-sourcing is dominant under low demand uncertainty. When demand uncertainty is high, sub-sourcing with buy-back may outperform direct sourcing given a moderate buy-back price.
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  • Optimal Contract Design for Mixed Channels Under Information Asymmetry

    Mukhopadhyay, Samar K.   Zhu, Xiaowei   Yue, Xiaohang  

    The mixed-charinel model is becoming increasingly Popular in the marketplace. In this model, a firm selling through the traditional supply chain of wholesaler and retailer opens a direct channel to the customer through Internet sales. Because both channels have their respective advantages, the manufacturer is attracted to this business model. However, it also leads to channel conflict, with the retailer feeling threatened by direct competition. One way of eliminating the possibility of this channel conflict, where the retailer is allowed to add value to the product to differentiate its offering to the customers, is proposed in this paper. The retailer is also given full authority to make pricing decisions. This paper presents a model, under this scenario, of obtaining optimum pricing decisions by both parties, the amount of value added by the retailer, and the manufacturer's wholesale price to the retailer. Our model incorporates information asymmetry, where the manufacturer has incomplete information about the retailer's cost of adding value. We obtain closed-form contracts with incomplete information and compare them with those with complete channel coordination. We also develop a number of managerial guidelines and identify future research topics.
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  • A Newsvendor Model with Autocorrelated Demand under A Time-Consistent Dynamic CVaR Measure

    Shi, Ye   Alwan, Layth   Tang, Siu (Christopher)   Yue, Xiaohang  

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  • Permutation Flow Shop Scheduling With Batch Delivery to Multiple Customers in Supply Chains

    Wang, Kai   Luo, Hao   Liu, Feng   Yue, Xiaohang  

    Rapid changes in production environments have motivated researchers and industrial manufacturers to coordinate the production and distribution in supply chain management. This paper aims to address the permutation flow shop scheduling problem with batch delivery to multiple customers. In this problem, products are first manufactured in a permutation flow shop, and subsequently delivered to multiple customers in batches. To optimize the tradeoff between customer service and distribution cost, the objective of this paper is to minimize the total cost of tardiness and batch delivery. To deal with such optimization problem, two simple heuristics and a novel meta-heuristic (GA-TVNS) are developed to determine integrated production and distribution schedules. GA-TVNS hybridizes genetic algorithm and variable neighborhood search (VNS) to provide better exploration and exploitation in the search space. Moreover, to improve the local search of VNS, two new learning-based neighborhood structures are designed based on the classical school learning process of teaching-learning-based optimization. Computation experiments on both small-sized and large-sized test problems indicate that GA-TVNS performs the best among all the compared scheduling algorithms.
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  • Vertical cost information sharing in a supply chain with value-adding retailers

    Yao, Dong-Qing   Yue, Xiaohang   Liu, John  

    We consider a supply chain consisting of one supplier and two value-adding heterogeneous retailers. Each retailer has full knowledge about his own value-added cost structure that is unknown to the supplier and the other retailer. Assuming there is no horizontal information sharing between two retailers, we model the supply chain with a three-stage game-theoretic framework. In the first stage each retailer decides if he is willing to vertically disclose his private cost information to the supplier. In the second stage, given the information he has about the retailers, the supplier announces the wholesale price to the retailers. In response to the wholesale price, in the third stage, the retailers optimize their own retail prices and the values added to the product, respectively. Under certain conditions, we prove the existence of equilibrium prices and added values. Furthermore, we obtain the condition under which both retailers are unwilling to vertically share their private information with the supplier, as well as the conditions under which both retailers have incentives to reveal their cost information to the supplier, thus leading to a win-win situation for the whole supply chain. (C) 2006 Elsevier Ltd. All rights reserved.
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  • Demand forecast sharing in a dual-channel supply chain

    Yue, Xiaohang   Liu, John  

    We assess the benefits of sharing demand forecast information in a manufacturer-retailer supply chain, consisting of a traditional retail channel and a direct channel. The demand is a linear function of price with a Gaussian primary demand (i.e., zero-price market potential). Both the manufacturer and the retailer set their price based on their forecast of the primary demand. In this setting, we investigate the value of sharing demand forecasts. We analyze the 'make-to-order' scenario, in which prices are set before and production takes place after the primary demand is known, and the 'make-to-stock' scenario, in which production takes place and prices are set before the primary demand is known. We also compare the supply chain performance with and without the direct channel under some assumptions (production cost is zero, and each demand function has the same slope of price). We find that the direct channel has a negative impact on the retailer's performance, and, under some conditions, the manufacturer and the whole supply chain are better off. Our research extends and complements prior research that has investigated only the inventory and replenishment-related benefits of information sharing. (c) 2005 Elsevier B.V. All rights reserved.
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  • A Bertrand model of pricing of complementary goods under information asymmetry

    Yue, Xiaohang   Mukhopadhyay, Samar K.   Zhu, Xiaowei  

    Parties in a supply chain, being independent firms, have private information about various aspects of the business not normally available to other parties. We consider a market where customers need to buy two complementary goods as mixed bundle, offered by two separate firms. The demand for each firm is dependent on the pricing strategy of both firms, which, in turn, depends on the quantities offered as per their own forecasts. We present a profit maximization model to obtain optimal strategies for a firm making decisions under information asymmetry. The model follows a simultaneously played Bertrand type game. We contrast and compare three scenarios: (1) when forecast information is asymmetric between the firms; (2) when forecast information is shared between the firms; and (3) when the firms form a strategic alliance. (c) 2006 Elsevier Inc. All rights reserved.
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