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Christopher S Tang - One of the best experts on this subject based on the ideXlab platform.
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win win Capacity Allocation contracts in co production and co distribution alliances
Management Science, 2017Co-Authors: Guillaume Roels, Christopher S TangAbstract:In some strategic alliances, a firm shares its manufacturing Capacity with another, and the latter shares its distribution Capacity with the former. Even though such bidirectional alliances have become common, they remain challenging to manage due to the frequent disputes over Capacity Allocation especially when demand is uncertain. In this paper, we investigate whether there exists a contractual mechanism that can mitigate the extent of these disputes while improving the profits of all participating firms. We consider two types of bidirectional contracts, namely, the ex-post transfer payment contract and the ex-ante Capacity reservation contract. By modeling the Capacity Allocation and the bidirectional contract design as a multi-stage game between two firms with non-competing product lines, we show that, relative to a situation where Capacity Allocation is freely negotiated, either contract can improve the alliance’s total profit in equilibrium. In terms of distribution of the total surplus, we find that Capacity reservation contracts always make both firms better off, whereas ex-post transfer payment contracts may make one firm worse off. Hence, Capacity reservation contracts are more likely to be implemented in practice in such co-production and co-distribution alliances.
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win win Capacity Allocation contracts in coproduction and codistribution alliances
Management Science, 2017Co-Authors: Guillaume Roels, Christopher S TangAbstract:In some strategic alliances, a firm shares its manufacturing Capacity with another, and the latter shares its distribution Capacity with the former. Even though such bidirectional alliances have become more common, they remain challenging to manage because of the frequent disputes over Capacity Allocation, especially when demand is uncertain. In this paper, we investigate whether there exists a contractual mechanism that can mitigate the extent of these disputes while improving the profits of all participating firms. We consider two types of bidirectional contracts, namely, the ex post transfer payment contract and the ex ante Capacity reservation contract. By modeling the Capacity Allocation and the bidirectional contract design as a noncooperative game between two firms with noncompeting product lines, we show that, relative to a situation with no contract, either contract can improve the alliance’s total profit in equilibrium. In terms of distribution of the total surplus, we find that Capacity reserva...
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technical note Capacity Allocation under retail competition uniform and competitive Allocations
Operations Research, 2014Co-Authors: Soohaeng Cho, Christopher S TangAbstract:When retailers' orders exceed the supplier's available Capacity, the supplier allocates his Capacity according to some Allocation rule. When retailers are local monopolists, uniform Allocation eliminates the “gaming effect” so that each retailer orders her ideal Allocation. However, when two retailers engage in Cournot competition under complete information, a recent study has shown that uniform Allocation fails to eliminate the gaming effect so that some retailer may inflate her order strategically. By examining a more general situation in which two or more retailers engage in Cournot competition under complete information, we establish exact conditions under which uniform Allocation fails to eliminate the gaming effect. These exact conditions enable us to construct a new rule called competitive Allocation that can eliminate the gaming effect. Without inflated orders from the retailers, the supplier's profit could be lower under competitive Allocation than under uniform Allocation when certain restrictive conditions hold. In contrast, competitive Allocation generates higher average profits for the retailers and for the supply chain; hence, it reduces the inefficiency of the decentralized supply chain.
David Tipper - One of the best experts on this subject based on the ideXlab platform.
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spare Capacity Allocation using partially disjoint paths for dual link failure protection
Design of Reliable Communication Networks, 2013Co-Authors: Victor Yu Liu, David TipperAbstract:A shared backup path protection (SBPP) scheme can be used to protect dual link failures by pre-planning each traffic flow with mutually disjoint working and two backup paths while minimizing the network overbuild. However, many existing backbone networks are bi-connected without three fully disjoint paths between all node pairs. Hence in practice partially disjoint paths (PDP) have been used for backup paths instead of fully disjoint ones. This paper studies the minimum spare Capacity Allocation (SCA) problem using PDP within an optimization framework. This is an extension of the spare provision matrix (SPM) method for PDP. The integer linear programming (ILP) model is formulated and an approximation algorithm, Successive Survivable Routing (SSR), is extended and used in the numerical study.
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Spare Capacity Allocation using shared backup path protection for dual link failures
Computer Communications, 2013Co-Authors: Victor Yu Liu, David TipperAbstract:This paper extends the spare Capacity Allocation (SCA) problem from single failures to dual link failures on mesh-like IP or WDM networks. The SCA problem pre-plans traffic flows with mutually disjoint one working and two backup paths using the shared backup path protection (SBPP) scheme. The spare provision matrix (SPM) method aggregates per-flow based information and computes the shared spare Capacity for dual link failures. When compared to previous two-flow based methods, it has better scalability and flexibility. The SCA problem is formulated as a non-linear integer programming model and partitioned into two sequential linear sub-models: one finds all primary backup paths, and the other finds all secondary backup paths. We extend the terminologies in the 1+1 and 1:1 link protection for the backup path protection: using '':'' to indicate backup paths with shared spare Capacity; and using ''+'' to indicate backup paths with dedicated Capacity. Numerical results from five networks show that the network redundancy of the 1+1+1 dedicated path protection is in the range of 313-400%. It drops to 96-180% in the 1:1:1 shared backup path protection without loss of dual-link resiliency, but with the trade-off of the highest complexity on spare Capacity shared by all backup paths. The 1+1:1 hybrid path protection provides intermediate redundancy at 187-310% with the moderate complexity. It has dedicated primary backup paths and shared secondary backup paths. We also compare passive sharing with active sharing. They perform spare Capacity sharing either after or during the backup path routing, i.e., the active sharing approach performs share spare Capacity within the backup path routing, while the passive sharing does so only after all backup paths are found. The active sharing approaches always achieve lower redundancy values than the passive sharing. The reduction percentages are about 12% for 1+1:1 and 25% for 1:1:1 respectively. The extension of the Successive Survivable Routing (SSR) heuristic algorithm to the dual failure case is given and the numerical results show that SSR maintains a 4-11% gap from optimal on small or medium networks, and scales up well on large networks.
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spare Capacity Allocation using shared backup path protection for dual link failures
Design of Reliable Communication Networks, 2011Co-Authors: Victor Yu Liu, David TipperAbstract:This paper extends the spare Capacity Allocation (SCA) problem from single link failure [1] to dual link failures on mesh-like IP or WDM networks. The SCA problem pre-plans traffic flows with mutually disjoint one working and two backup paths using the shared backup path protection (SBPP) scheme. The aggregated spare provision matrix (SPM) is used to capture the spare Capacity sharing for dual link failures. Comparing to a previous work by He and Somani [2], this method has better scalability and flexibility. The SCA problem is formulated in a non-linear integer programming model and partitioned into two sequential linear sub-models: one finds all primary backup paths first, and the other finds all secondary backup paths next. The results on five networks show that the network redundancy using dedicated 1+1+1 is in the range of 313–400%. It drops to 96–181% in 1:1:1 without loss of dual-link resiliency, but with the trade-off of using the complicated share Capacity sharing among backup paths. The hybrid 1+1:1 provides intermediate redundancy ratio at 187–310% with a moderate complexity. We also compare the passive/active approaches which consider spare Capacity sharing after/during the backup path routing process. The active sharing approaches always achieve lower redundancy values than the passive ones. These reduction percentages are about 12% for 1+1:1 and 25% for 1:1:1 respectively.
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Spare Capacity Allocation in Two-Layer Networks
IEEE Journal on Selected Areas in Communications, 2007Co-Authors: Yu Liu, David Tipper, K. VajanapoomAbstract:In this paper we consider the problem of provisioning spare Capacity in two-layer backbone networks using shared backup path protection. First, two spare Capacity Allocation (SCA) optimization problems are formulated as integer linear programming (ILP) models for the cases of protection at the top layer against failures at the bottom layer. The first model captures failure propagation using overlay information between two layers for backup paths to meet diversity requirements. The second model improves bandwidth efficiency by moving spare Capacity sharing from the top layer to the bottom layer. This exposes a tradeoff between bandwidth efficiency and extra cross-layer operation. Next, the SCA model for common pool protection is developed to allow spare Capacity sharing between two layers. Our previous SCA heuristic technique, successive survivable routing (SSR) is extended for these optimization problems. Numerical results for a variety of networks indicate that the common pool protection is attractive to enhance bandwidth efficiency without loss of survivability and that the SSR heuristic quickly results in near optimal solutions
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approximating optimal spare Capacity Allocation by successive survivable routing
IEEE ACM Transactions on Networking, 2005Co-Authors: Yu Liu, David Tipper, Peerapon SiripongwutikornAbstract:The design of survivable mesh based communication networks has received considerable attention in recent years. One task is to route backup paths and allocate spare Capacity in the network to guarantee seamless communications services survivable to a set of failure scenarios. This is a complex multi-constraint optimization problem, called the spare Capacity Allocation (SCA) problem. This paper unravels the SCA problem structure using a matrix-based model, and develops a fast and efficient approximation algorithm, termed successive survivable routing (SSR). First, per-flow spare Capacity sharing is captured by a spare provision matrix (SPM) method. The SPM matrix has a dimension the number of failure scenarios by the number of links. It is used by each demand to route the backup path and share spare Capacity with other backup paths. Next, based on a special link metric calculated from SPM, SSR iteratively routes/updates backup paths in order to minimize the cost of total spare Capacity. A backup path can be further updated as long as it is not carrying any traffic. Furthermore, the SPM method and SSR algorithm are generalized from protecting all single link failures to any arbitrary link failures such as those generated by Shared Risk Link Groups or all single node failures. Numerical results comparing several SCA algorithms show that SSR has the best trade-off between solution optimality and computation speed.
Guillaume Roels - One of the best experts on this subject based on the ideXlab platform.
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win win Capacity Allocation contracts in co production and co distribution alliances
Management Science, 2017Co-Authors: Guillaume Roels, Christopher S TangAbstract:In some strategic alliances, a firm shares its manufacturing Capacity with another, and the latter shares its distribution Capacity with the former. Even though such bidirectional alliances have become common, they remain challenging to manage due to the frequent disputes over Capacity Allocation especially when demand is uncertain. In this paper, we investigate whether there exists a contractual mechanism that can mitigate the extent of these disputes while improving the profits of all participating firms. We consider two types of bidirectional contracts, namely, the ex-post transfer payment contract and the ex-ante Capacity reservation contract. By modeling the Capacity Allocation and the bidirectional contract design as a multi-stage game between two firms with non-competing product lines, we show that, relative to a situation where Capacity Allocation is freely negotiated, either contract can improve the alliance’s total profit in equilibrium. In terms of distribution of the total surplus, we find that Capacity reservation contracts always make both firms better off, whereas ex-post transfer payment contracts may make one firm worse off. Hence, Capacity reservation contracts are more likely to be implemented in practice in such co-production and co-distribution alliances.
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win win Capacity Allocation contracts in coproduction and codistribution alliances
Management Science, 2017Co-Authors: Guillaume Roels, Christopher S TangAbstract:In some strategic alliances, a firm shares its manufacturing Capacity with another, and the latter shares its distribution Capacity with the former. Even though such bidirectional alliances have become more common, they remain challenging to manage because of the frequent disputes over Capacity Allocation, especially when demand is uncertain. In this paper, we investigate whether there exists a contractual mechanism that can mitigate the extent of these disputes while improving the profits of all participating firms. We consider two types of bidirectional contracts, namely, the ex post transfer payment contract and the ex ante Capacity reservation contract. By modeling the Capacity Allocation and the bidirectional contract design as a noncooperative game between two firms with noncompeting product lines, we show that, relative to a situation with no contract, either contract can improve the alliance’s total profit in equilibrium. In terms of distribution of the total surplus, we find that Capacity reserva...
Yiping Dai - One of the best experts on this subject based on the ideXlab platform.
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Capacity Allocation of a hybrid energy storage system for power system peak shaving at high wind power penetration level
Renewable Energy, 2015Co-Authors: Pan Zhao, Jiangfeng Wang, Yiping DaiAbstract:High wind power penetration in power system leads to a significant challenge in balancing power production and consumption due to the intermittence of wind. Introducing energy storage system in wind energy system can help offset the negative effects, and make the wind power controllable. However, the power spectrum density of wind power outputs shows that the fluctuations of wind energy include various components with different frequencies and amplitudes. This implies that the hybrid energy storage system is more suitable for smoothing out the wind power fluctuations effectively rather than the independent energy storage system. In this paper, we proposed a preliminary scheme for Capacity Allocation of hybrid energy storage system for power system peak shaving by using spectral analysis method. The unbalance power generated from load dispatch plan and wind power outputs is decomposed into four components, which are outer-day, intra-day, short-term and very short-term components, by using Discrete Fourier Transform (DFT) and spectral decomposition method. The Capacity Allocation can be quantified according to the information in these components. The simulation results show that the power rating and energy rating of hybrid energy storage system in partial smoothing mode decrease significantly in comparison with those in fully smoothing mode.
Steve Samuelson - One of the best experts on this subject based on the ideXlab platform.
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improving health outcomes through better Capacity Allocation in a community based chronic care model
Deo S Iravani S Jiang T Smilowitz K Samuelson S., 2014Co-Authors: Sarang Deo, Seyed M R Iravani, Tingting Jiang, Karen Smilowitz, Steve SamuelsonAbstract:This paper studies a model of community-based healthcare delivery for a chronic disease. In this setting, patients periodically visit the healthcare delivery system, which influences their disease progression and consequently their health outcomes.
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improving health outcomes through better Capacity Allocation in a community based chronic care model
Operations Research, 2013Co-Authors: Sarang Deo, Seyed M R Iravani, Tingting Jiang, Karen Smilowitz, Steve SamuelsonAbstract:This paper studies a model of community-based healthcare delivery for a chronic disease. In this setting, patients periodically visit the healthcare delivery system, which influences their disease progression and consequently their health outcomes. We investigate how the provider can maximize community-level health outcomes through better operational decisions pertaining to Capacity Allocation across different patients. To do so, we develop an integrated Capacity Allocation model that incorporates clinical (disease progression) and operational (Capacity constraint) aspects. Specifically, we model the provider's problem as a finite horizon stochastic dynamic program, where the provider decides which patients to schedule at the beginning of each period. Therapy is provided to scheduled patients, which may improve their health states. Patients that are not seen follow their natural disease progression. We derive a quantitative measure for comparison of patients' health states and use it to design an easy-to-...
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improving health outcomes through better Capacity Allocation in a community based chronic care model
Social Science Research Network, 2013Co-Authors: Sarang Deo, Seyed M R Iravani, Tingting Jiang, Karen Smilowitz, Steve SamuelsonAbstract:This paper studies a model of community-based healthcare delivery for a chronic disease. In this setting, patients periodically visit the healthcare delivery system, which influences their disease progression and consequently their health outcomes. We investigate how the provider can maximize community-level health outcomes through better operational decisions pertaining to Capacity Allocation across different patients. To do so, we develop an integrated Capacity Allocation model that incorporates clinical (disease progression) and operational (Capacity constraint) aspects. Specifically, we model the provider's problem as a finite horizon stochastic dynamic program, where the provider decides which patients to schedule at the beginning of each period. Therapy is provided to scheduled patients, which may improve their health states. Patients that are not seen follow their natural disease progression. We derive a quantitative measure for comparison of patients' health states and use it to design an easy-to-implement myopic heuristic that is provably optimal in special cases of the problem. We employ the myopic heuristic in a more general setting and test its performance using operational and clinical data obtained from Mobile C.A.R.E. Foundation, a community-based provider of pediatric asthma care in Chicago. Our extensive computational experiments suggest that the myopic heuristic can improve the health gains at the community level by up to 15% over the current policy. The benefit is driven by the ability of our myopic heuristic to alter the duration between visits for patients with different health states depending on the tightness of the Capacity and the health states of the entire patient population.
