17 results on '"Zuo, Jun"'
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2. Role of resource flexibility and responsive pricing in mitigating the uncertainties in production systems
- Author
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Hariharan, Sharethram, Liu, Tieming, and Shen, Zuo-Jun Max
- Published
- 2020
- Full Text
- View/download PDF
3. An automated planning engine for biopharmaceutical production
- Author
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Leachman, Robert C., Johnston, Lenrick, Li, Shan, and Shen, Zuo-Jun
- Published
- 2014
- Full Text
- View/download PDF
4. Role of resource flexibility and responsive pricing in mitigating the uncertainties in production systems
- Author
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Sharethram Hariharan, Tieming Liu, and Zuo-Jun Max Shen
- Subjects
Flexibility (engineering) ,050210 logistics & transportation ,Strategic dominance ,021103 operations research ,Information Systems and Management ,Supply chain management ,General Computer Science ,05 social sciences ,0211 other engineering and technologies ,02 engineering and technology ,Management Science and Operations Research ,Investment (macroeconomics) ,Industrial and Manufacturing Engineering ,Resource (project management) ,Modeling and Simulation ,0502 economics and business ,Value (economics) ,Production (economics) ,Risk pool ,Business ,Industrial organization - Abstract
Two effective strategies that mitigate a firm’s demand risk are resource flexibility investment and responsive pricing. In addition to demand uncertainties firms also face capacity uncertainties and capacity disruptions and the effectiveness of these strategies under these risks are less clear. We investigate the value of resource flexibility and responsive pricing under different risk settings for a firm that produces two substitutable products each with its own dedicated resource that can be optionally reconfigured to produce the other product. Reconfiguration or cross-production incurs efficiency loss which can be mitigated by choosing the degree of flexibility of these resources, at a cost, in the planning stage along with capacity levels. In the production stage, after capacities and market potentials are realized, the firm allocates resources and sets prices. We find that under only demand uncertainties the value of flexibility is very low and only a moderate degree of flexibility is sufficient under high demand risk. Responsive pricing is the dominant strategy as the firm avoids investment in costly flexibility. When facing both demand and capacity uncertainties the firm invests in higher levels of flexibility but the value of flexibility is lower than the value of responsive pricing. However, under demand and capacity disruptions flexibility arises as the dominant strategy due to the resource risk pooling effect and the value of flexibility eclipses the value of pricing as the firm invests in full flexibility. For a firm with responsive pricing investment in flexibility is economically justified under high capacity uncertainties and capacity disruptions.
- Published
- 2020
5. Fix-and-optimize heuristics for capacitated lot-sizing with sequence-dependent setups and substitutions
- Author
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Lang, Jan Christian and Shen, Zuo-Jun Max
- Published
- 2011
- Full Text
- View/download PDF
6. Inventory systems with stochastic demand and supply: Properties and approximations
- Author
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Schmitt, Amanda J., Snyder, Lawrence V., and Shen, Zuo-Jun Max
- Published
- 2010
- Full Text
- View/download PDF
7. Worst-case analysis of demand point aggregation for the Euclidean p-median problem
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Qi, Lian and Shen, Zuo-Jun Max
- Published
- 2010
- Full Text
- View/download PDF
8. Planning and approximation models for delivery route based services with price-sensitive demands
- Author
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Geunes, Joseph, Shen, Zuo-Jun Max, and Emir, Akin
- Subjects
Business ,Business, general ,Business, international - Abstract
To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2006.07.010 Byline: Joseph Geunes (a), Zuo-Jun Max Shen (b), Akin Emir (c) Keywords: Revenue management; Pricing; Vehicle routing problem Abstract: Classical vehicle routing problems typically do not consider the impact of delivery price on the demand for delivery services. Existing models seek the minimum sum of tour lengths in order to serve the demands of a given set of customers. This paper proposes approximation models to estimate the impacts of price on delivery services when demand for delivery service is price dependent. Such models can serve as useful tools in the planning phase for delivery service providers and can assist in understanding the economics of delivery services. These models seek to maximize profit from delivery service, where price determines demand for deliveries as well as the total revenue generated by satisfying demand. We consider a variant of the model in which each customer's delivery volume is price sensitive, as well as the case in which customer delivery volumes are fixed, but the total number of customers who select the delivery service provider is price sensitive. A third model variant allows the delivery service provider to select a subset of delivery requests at the offered price in order to maximize profit. Author Affiliation: (a) Department of Industrial and Systems Engineering, University of Florida, United States (b) Department of Industrial Engineering and Operations Research, University of California, 4141 Etcheverry Hall, Berkeley, CA 94720-1777, United States (c) Merck and Co., Inc., West Point, PA, United States Article History: Received 5 January 2006; Accepted 17 July 2006
- Published
- 2007
9. Trade reduction vs. multi-stage: A comparison of double auction design approaches
- Author
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Chu, Leon Yang and Shen, Zuo-Jun Max
- Subjects
Auctions -- Analysis ,Business ,Business, general ,Business, international - Abstract
To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2006.04.015 Byline: Leon Yang Chu (a)(b), Zuo-Jun Max Shen (b) Keywords: Mechanism design; Double auction; Strategy-proof mechanism Abstract: With the growth of electronic markets, designing double auction mechanisms that are applicable to emerging market structures has become an important research topic. In this paper, we investigate two truthful double auction design approaches, the Trade Reduction Approach and the Multi-Stage Design Approach, and compare their resulting mechanisms in various exchange environments. We find that comparing with the Trade Reduction Approach, the Multi-Stage Design Approach offers mechanisms applicable to more complicated exchange environments. Furthermore, for the known trade reduction mechanisms, we prove that the corresponding mechanisms under the multi-stage design approach are superior in terms of both social efficiency and individual payoffs, in each exchange environment of interest. Our computational tests show that the mechanisms under the multi-stage design approach achieve very high efficiency in various scenarios. Author Affiliation: (a) Marshall School of Business, University of South California, Los Angeles, CA 90089, United States (b) Department of Industrial Engineering and Operations Research, University of California, Berkeley, CA 94720, United States Article History: Received 23 May 2005; Accepted 3 April 2006
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- 2007
10. Incorporating inventory and routing costs in strategic location models
- Author
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Shen, Zuo-Jun Max and Qi, Lian
- Subjects
Algorithms -- Analysis ,Logistics -- Analysis ,Management science -- Analysis ,Algorithm ,Business ,Business, general ,Business, international - Abstract
To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2006.03.032 Byline: Zuo-Jun Max Shen (a), Lian Qi (b) Keywords: Location models; Vehicle routing; Inventory; Integrated supply chain design models Abstract: We consider a supply chain design problem where the decision maker needs to decide the number and locations of the distribution centers (DCs). Customers face random demand, and each DC maintains a certain amount of safety stock in order to achieve a certain service level for the customers it serves. The objective is to minimize the total cost that includes location costs and inventory costs at the DCs, and distribution costs in the supply chain. We show that this problem can be formulated as a nonlinear integer programming model, for which we propose a Lagrangian relaxation based solution algorithm. By exploring the structure of the problem, we find a low-order polynomial algorithm for the nonlinear integer programming problem that must be solved in solving the Lagrangian relaxation sub-problems. We present computational results for several instances of the problem with sizes ranging from 40 to 320 customers. Our results show the benefits of having an integrated supply chain design framework that includes location, inventory, and routing decisions in the same optimization model. Author Affiliation: (a) Department of Industrial Engineering and Operations Research, University of California, 4141 Etcheverry Hall, Berkeley, CA 94720-1777, USA (b) Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA Article History: Received 9 March 2005; Accepted 25 March 2006
- Published
- 2007
11. Incorporating inventory and routing costs in strategic location models
- Author
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Max Shen, Zuo-Jun and Qi, Lian
- Published
- 2007
- Full Text
- View/download PDF
12. An automated planning engine for biopharmaceutical production
- Author
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Zuo-Jun Max Shen, Lenrick Johnston, Shan Li, and Robert C. Leachman
- Subjects
Schedule ,Information Systems and Management ,General Computer Science ,Computer science ,media_common.quotation_subject ,Supply chain ,Scheduling (production processes) ,Management Science and Operations Research ,Industrial and Manufacturing Engineering ,Manufacturing engineering ,Product (business) ,Production planning ,Modeling and Simulation ,Batch processing ,Production (economics) ,Operations management ,Quality (business) ,Biomanufacturing ,media_common - Abstract
We introduce an optimization-based production planning tool for the biotechnology industry. The industry’s planning problem is unusually challenging because the entire production process is regulated by multiple external agencies – such as the US Food and Drug Administration – representing countries where the biopharmaceutical is to be sold. The model is structured to precisely capture the constraints imposed by current and projected regulatory approvals of processes and facilities, as well as capturing the outcomes of quality testing and processing options, facility capacities and initial status of work-in-process. The result is a supply chain “Planning Engine” that generates capacity-feasible batch processing schedules for each production facility within the biomanufacturing supply chain and an availability schedule for finished product against a known set of demands and regulations. Developing the formulation based on distinct time grids tailored for each facility, planning problems with more than 27,000 boolean variables, more than 130,000 linear variables and more than 80,000 constraints are automatically formulated and solved within a few hours. The Planning Engine’s development and implementation at Bayer Healthcare’s Berkeley, CA manufacturing site is described.
- Published
- 2014
13. Fix-and-optimize heuristics for capacitated lot-sizing with sequence-dependent setups and substitutions
- Author
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Jan Christian Lang and Zuo-Jun Max Shen
- Subjects
Scheme (programming language) ,Mathematical optimization ,Information Systems and Management ,General Computer Science ,Computer science ,Computation ,Management Science and Operations Research ,Solver ,Industrial and Manufacturing Engineering ,Sizing ,Production planning ,Modeling and Simulation ,Decomposition (computer science) ,Heuristics ,computer ,Integer programming ,computer.programming_language - Abstract
In this paper, we consider a capacitated single-level dynamic lot-sizing problem with sequence-dependent setup costs and times that includes product substitution options. The model is motivated from a real-world production planning problem of a manufacturer of plastic sheets used as an interlayer in car windshields. We develop a mixed-integer programming (MIP) formulation of the problem and devise MIP-based Relax&Fix and Fix&Optimize heuristics. Unlike existing literature, we combine Fix&Optimize with a time decomposition. Also, we develop a specialized substitute decomposition and devise a computation budget allocation scheme for ensuring a uniform, efficient usage of computation time by decompositions and their subproblems. Computational experiments were performed on generated instances whose structure follows that of the considered practical application and which have rather tight production capacities. We found that a Fix&Optimize algorithm with an overlapping time decomposition yielded the best solutions. It outperformed the state-of-the-art approach Relax&Fix and all other tested algorithm variants on the considered class of instances, and returned feasible solutions with neither overtime nor backlogging for all instances. It returned solutions that were on average only 5% worse than those returned by a standard MIP solver after 4 hours and 19% better than those of Relax&Fix.
- Published
- 2011
14. Worst-case analysis of demand point aggregation for the Euclidean p-median problem
- Author
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Zuo-Jun Max Shen and Lian Qi
- Subjects
Mathematical optimization ,Information Systems and Management ,General Computer Science ,Demand point ,Heuristic (computer science) ,Aggregate (data warehouse) ,Management Science and Operations Research ,Industrial and Manufacturing Engineering ,Modeling and Simulation ,On demand ,Euclidean geometry ,Point (geometry) ,Probabilistic analysis of algorithms ,Case analysis ,Mathematics - Abstract
Solving large-scale p -median problems is usually time consuming. People often aggregate the demand points in a large-scale p -median problem to reduce its problem size and make it easier to solve. Most traditional research on demand point aggregation is either experimental or assuming uniformly distributed demand points in analytical studies. In this paper, we study demand point aggregation for planar p -median problem when demand points are arbitrarily distributed. Efficient demand aggregation approaches are proposed with the corresponding attainable worst-case aggregation error bounds measured. We demonstrate that these demand aggregation approaches introduce smaller worst-case aggregation error bounds than that of the honeycomb heuristic [Papadimitriou, C.H., 1981. Worst-case and probabilistic analysis of a geometric location problem. SIAM Journal on Computing 10, 542–557] when demand points are arbitrarily distributed. We also conduct numerical experiments to show their effectiveness.
- Published
- 2010
15. Planning and approximation models for delivery route based services with price-sensitive demands
- Author
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Joseph Geunes, Akin Emir, and Zuo-Jun Max Shen
- Subjects
Information Systems and Management ,General Computer Science ,Operations research ,Service delivery framework ,Total revenue ,Management Science and Operations Research ,Service provider ,Industrial and Manufacturing Engineering ,Profit (economics) ,Modeling and Simulation ,Approximation models ,Vehicle routing problem ,Economics ,Operations management ,Best-effort delivery - Abstract
Classical vehicle routing problems typically do not consider the impact of delivery price on the demand for delivery services. Existing models seek the minimum sum of tour lengths in order to serve the demands of a given set of customers. This paper proposes approximation models to estimate the impacts of price on delivery services when demand for delivery service is price dependent. Such models can serve as useful tools in the planning phase for delivery service providers and can assist in understanding the economics of delivery services. These models seek to maximize profit from delivery service, where price determines demand for deliveries as well as the total revenue generated by satisfying demand. We consider a variant of the model in which each customer’s delivery volume is price sensitive, as well as the case in which customer delivery volumes are fixed, but the total number of customers who select the delivery service provider is price sensitive. A third model variant allows the delivery service provider to select a subset of delivery requests at the offered price in order to maximize profit.
- Published
- 2007
16. Trade reduction vs. multi-stage: A comparison of double auction design approaches
- Author
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Leon Yang Chu and Zuo-Jun Max Shen
- Subjects
Mechanism design ,Mathematical optimization ,Information Systems and Management ,General Computer Science ,Management Science and Operations Research ,Social efficiency ,Bidding ,Industrial and Manufacturing Engineering ,Multi stage ,Reduction (complexity) ,Market structure ,Modeling and Simulation ,Economics ,Double auction ,Emerging markets ,Industrial organization - Abstract
With the growth of electronic markets, designing double auction mechanisms that are applicable to emerging market structures has become an important research topic. In this paper, we investigate two truthful double auction design approaches, the Trade Reduction Approach and the Multi-Stage Design Approach, and compare their resulting mechanisms in various exchange environments. We find that comparing with the Trade Reduction Approach, the Multi-Stage Design Approach offers mechanisms applicable to more complicated exchange environments. Furthermore, for the known trade reduction mechanisms, we prove that the corresponding mechanisms under the multi-stage design approach are superior in terms of both social efficiency and individual payoffs, in each exchange environment of interest. Our computational tests show that the mechanisms under the multi-stage design approach achieve very high efficiency in various scenarios.
- Published
- 2007
17. Incorporating inventory and routing costs in strategic location models
- Author
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Lian Qi and Zuo-Jun Max Shen
- Subjects
Mathematical optimization ,Information Systems and Management ,General Computer Science ,Supply chain ,Management Science and Operations Research ,Industrial and Manufacturing Engineering ,Nonlinear programming ,symbols.namesake ,Safety stock ,Lagrangian relaxation ,Modeling and Simulation ,Service level ,Vehicle routing problem ,Inventory theory ,symbols ,Integer programming ,Mathematics - Abstract
We consider a supply chain design problem where the decision maker needs to decide the number and locations of the distribution centers (DCs). Customers face random demand, and each DC maintains a certain amount of safety stock in order to achieve a certain service level for the customers it serves. The objective is to minimize the total cost that includes location costs and inventory costs at the DCs, and distribution costs in the supply chain. We show that this problem can be formulated as a nonlinear integer programming model, for which we propose a Lagrangian relaxation based solution algorithm. By exploring the structure of the problem, we find a low-order polynomial algorithm for the nonlinear integer programming problem that must be solved in solving the Lagrangian relaxation sub-problems. We present computational results for several instances of the problem with sizes ranging from 40 to 320 customers. Our results show the benefits of having an integrated supply chain design framework that includes location, inventory, and routing decisions in the same optimization model.
- Published
- 2007
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