This page has only limited features, please log in for full access.
In the traditional single-machine scheduling problem with uncertain processing time, distributionally robust optimization models are established in situations where the distribution information is not known exactly. One well-studied robust optimization method used in scheduling is the distributionally β-robust optimization technique. The goal of this technique is to maximize the probability that the total flow time of the job sequence does not exceed the predetermined target level T. However, it is possible that the excess value of the total flow time beyond the target T may be incredibly large, and therefore it is necessary to consider the optimized excess value. To address this concern, two new target-based risk measures are introduced. First, target-oriented CVaR, the worst-case conditional value-at-risk (CVaR) is used to minimize the excess value beyond T, which accounts for both the excess probability and the excess value. Second, the essential riskiness index (ERI) is extended to a multi-piecewise linear function for excess value control in single-machine scheduling problems. To obtain a tractable closed-form solutions of the risk measures, the CVaR-based measure is decomposed into an assignment problem and a second-order cone programming problem, and the ERI is converted to its equivalent semi-definite programming and second-order cone counterparts. To efficiently solve the risk measures for single-machine scheduling, a bisection search algorithm and a Benders decomposition algorithm are designed. In the numerical analysis, the excess value and the probability are investigated with respect to two distributions, namely the two-point distribution and the truncated normal distribution. The experiment design also considers different ranges of expectation and variance, tolerance levels, and problem scales. It is discovered that the CVaR and ERI-based methods are always better than the distributionally β-robust scheduling approach in terms of excess value.
Zhi Pei; Haimin Lu; Qingwei Jin; Lianmin Zhang. Target-based Distributionally Robust Optimization for Single Machine Scheduling. European Journal of Operational Research 2021, 1 .
AMA StyleZhi Pei, Haimin Lu, Qingwei Jin, Lianmin Zhang. Target-based Distributionally Robust Optimization for Single Machine Scheduling. European Journal of Operational Research. 2021; ():1.
Chicago/Turabian StyleZhi Pei; Haimin Lu; Qingwei Jin; Lianmin Zhang. 2021. "Target-based Distributionally Robust Optimization for Single Machine Scheduling." European Journal of Operational Research , no. : 1.
As a well-developed optimization problem, the knapsack problem has been broadly applied in various fields involving resource allocations, especially production planning. In this paper, we propose a target-based distributionally robust knapsack problem (TDRKP), considering both uncertain profit and capacity, as well as the impact of a given target for profit. Based on a shortfall risk measure and piecewise utility function, the violation risk of the target is investigated. To solve the model efficiently, TDRKP is reformulated into computationally tractable form as a second-order conic program. Through a series of numerical experiments, we verify that the proposed TDRKP formulation performs better than both the sample average approximation model and the minimizing violation probabilities model.
Jianpeng Ding; Liuxin Chen; Ginger Y. Ke; Yuanbo Li; Lianmin Zhang. Balancing the profit and capacity under uncertainties: a target‐based distributionally robust knapsack problem. International Transactions in Operational Research 2021, 1 .
AMA StyleJianpeng Ding, Liuxin Chen, Ginger Y. Ke, Yuanbo Li, Lianmin Zhang. Balancing the profit and capacity under uncertainties: a target‐based distributionally robust knapsack problem. International Transactions in Operational Research. 2021; ():1.
Chicago/Turabian StyleJianpeng Ding; Liuxin Chen; Ginger Y. Ke; Yuanbo Li; Lianmin Zhang. 2021. "Balancing the profit and capacity under uncertainties: a target‐based distributionally robust knapsack problem." International Transactions in Operational Research , no. : 1.
In this article, we investigate the pricing optimization of firms selling multiple alternatives to the market where consumer purchase behavior follows the linear nested stochastic choice (LNSC) model. As a special case of the nested stochastic choice (NSC) model, LNSC similarly features a two-step Luce procedure. Considering differentiated price sensitivities in a non-exact preference function form, the present research specifically shows that, for any product in each nest, the adjusted markup is constant under certain conditions; and the adjusted nest-level markup is constant among nests under another sufficient condition. The “loss-leader” effect is observed, which indicates that it may be optimal to price a product with a negative adjusted markup or even a negative margin to attract more attention to the corresponding nest. Based on these results, the pricing optimization can be simplified to a single-variable problem where the objective function is unimodal. Then, a special case with an exponential preference function is discussed along with its concavity of the total expected profit. The above results are also used to construct the oligopoly multiproduct price competition and characterize the Nash equilibrium. Finally, a series of sensitivity analyses are conducted to reveal the impacts of key parameters on the optimal solutions.
Lixiang Li; Ginger Y. Ke; Min Li; Lianmin Zhang. Pricing optimization and competition under the linear nested stochastic choice model. Naval Research Logistics (NRL) 2021, 1 .
AMA StyleLixiang Li, Ginger Y. Ke, Min Li, Lianmin Zhang. Pricing optimization and competition under the linear nested stochastic choice model. Naval Research Logistics (NRL). 2021; ():1.
Chicago/Turabian StyleLixiang Li; Ginger Y. Ke; Min Li; Lianmin Zhang. 2021. "Pricing optimization and competition under the linear nested stochastic choice model." Naval Research Logistics (NRL) , no. : 1.
Technologies have been driving improvements in logistics and transportation. Focusing on a third-party logistics (3PL) firm’s technology innovations supported by external equity financing, we examine how the innovations can benefit the supply chain, and how the supply chain members should respond with coordinated operational decisions. More specifically, we consider a platform supply chain where a supplier sells a single product on an online platform provided by a retailer, and then hires a 3PL firm for transportation services. The 3PL firm may choose to raise capital through equity financing from external financial institutions, which can be used to support technology innovations to reduce the transportation cost. The financing decision of the 3PL interacts with operational decisions of the platform supply chain via possible cost savings. We start with investigating the supply chain coordination by characterizing the optimal operational decisions of the three firms under any given equity financing strategy. Acting non-cooperatively, the 3PL firm and the online retailer first determine the freight charge and revenue sharing respectively, in light of which the supplier’s decision on the retail price. We then move to the 3PL firm internally and derive the optimal equity financing strategy. Our analytical results show that the supply chain efficiency is dependent on the cost allocation between the retailer and the other two firms, but independent of the cost allocation between those two firms. It is also revealed that the original shareholders of the 3PL firm always have a chance to benefit from an appropriate financing strategy, and the optimal financing strategy may depend discontinuously on supply chain parameters. Finally, we check the robustness of our model and show that all key findings remain unchanged when relaxing the deterministic cost reduction to an uncertain one.
Hong Fu; Ginger Y. Ke; Zhaotong Lian; Lianmin Zhang. 3PL firm’s equity financing for technology innovation in a platform supply chain. Transportation Research Part E: Logistics and Transportation Review 2021, 147, 102239 .
AMA StyleHong Fu, Ginger Y. Ke, Zhaotong Lian, Lianmin Zhang. 3PL firm’s equity financing for technology innovation in a platform supply chain. Transportation Research Part E: Logistics and Transportation Review. 2021; 147 ():102239.
Chicago/Turabian StyleHong Fu; Ginger Y. Ke; Zhaotong Lian; Lianmin Zhang. 2021. "3PL firm’s equity financing for technology innovation in a platform supply chain." Transportation Research Part E: Logistics and Transportation Review 147, no. : 102239.
Project control that aims to track the project performance and to expedite relevant tasks when necessary has become the main aspect to ensure a successful scheduling outcome. We consider a project crashing problem with task completion due date. To cope with uncertainties lie in the duration time of tasks, we can crash the task with outsourced capacities, which should be reserved during the project planning stage. The total cost, including both capacity reservation cost and crashing cost, should be no more than the project budget. Since meeting with the task due date is a natural target, we focus on minimizing the overall task delay risk and model the objective using the target-based measure of minimizing delay risk index (DRI). We establish an adaptive distributionally robust optimization (ADRO) model for the project crashing problem and translate it into an equivalent mixed integer programming model. We compare the performance of our model against the stochastic approach and the expected makespan minimization model. Our model shows more efficiency and robustness with only mean and support information.
Yuanbo Li; Zheng Cui; Houcai Shen; Lianmin Zhang. Target-based project crashing problem by adaptive distributionally robust optimization. Computers & Industrial Engineering 2021, 157, 107160 .
AMA StyleYuanbo Li, Zheng Cui, Houcai Shen, Lianmin Zhang. Target-based project crashing problem by adaptive distributionally robust optimization. Computers & Industrial Engineering. 2021; 157 ():107160.
Chicago/Turabian StyleYuanbo Li; Zheng Cui; Houcai Shen; Lianmin Zhang. 2021. "Target-based project crashing problem by adaptive distributionally robust optimization." Computers & Industrial Engineering 157, no. : 107160.
We study a problem in which independent project managers cooperate to generate additional revenue by reallocating their resources. This additional revenue equals the increase in the direct return of a project minus the resource transfer cost. For each project, its direct return is closely related to its duration, which is mainly determined by the amount of resources available. In practice, the relationship between direct return and resources can be very complex. We study the situation that all projects use one same type of continuously divisible renewable resource and require some other types of discrete renewable resources. The activity processing rate of a project depends on its continuous resource and can be linear, strictly concave, or convex. The direct return of a project is linear over time. Based on results reported in the literature, we first show that it is not uncommon for the direct return of a project to be concave in relation to the amount of resources. Then, we formulate the resource transfer problem (RTP) as a convex programming problem and derive interesting properties. Furthermore, we design a revenue sharing scheme, which is in the core of a corresponding cooperative game. Finally, we conduct numerical experiments to show the value of cooperation, examine the efficiency of the proposed additional revenue sharing scheme, and evaluate the effects of the transfer cost, the unit time reward/penalty, and the amount of initial resource.
Xiaowei Lin; Xiaoqiang Cai; Lianmin Zhang; Jing Zhou; Yinlian Zeng. Revenue sharing for resource transfer among projects. Computers & Operations Research 2020, 127, 105156 .
AMA StyleXiaowei Lin, Xiaoqiang Cai, Lianmin Zhang, Jing Zhou, Yinlian Zeng. Revenue sharing for resource transfer among projects. Computers & Operations Research. 2020; 127 ():105156.
Chicago/Turabian StyleXiaowei Lin; Xiaoqiang Cai; Lianmin Zhang; Jing Zhou; Yinlian Zeng. 2020. "Revenue sharing for resource transfer among projects." Computers & Operations Research 127, no. : 105156.
This paper analyses a multi-period single-item repairable inventory system with stochastic new and warranty demands. We assume that newly-procured items are indistinguishable from items repaired from repairable warranty returns and new demand has higher priority than warranty demand within a period. Our model also captures the “repair loss” in repairing returns in each period. We formulate the problem by a dynamic programme, and prove that the optimal policy is completely defined by three period-dependent thresholds: the purchase-up-to level, the repair-up-to level, and the scrap-down-to level. Numerical results demonstrate the effectiveness of the optimal policy and show that our optimal strategy outperforms the repair-all strategy and no-repair strategy. Managerial insights are also generated.
Yizhong Lin; Janny M.Y. Leung; Lianmin Zhang; Jia-Wen Gu. Single-item repairable inventory system with stochastic new and warranty demands. Transportation Research Part E: Logistics and Transportation Review 2020, 142, 102035 .
AMA StyleYizhong Lin, Janny M.Y. Leung, Lianmin Zhang, Jia-Wen Gu. Single-item repairable inventory system with stochastic new and warranty demands. Transportation Research Part E: Logistics and Transportation Review. 2020; 142 ():102035.
Chicago/Turabian StyleYizhong Lin; Janny M.Y. Leung; Lianmin Zhang; Jia-Wen Gu. 2020. "Single-item repairable inventory system with stochastic new and warranty demands." Transportation Research Part E: Logistics and Transportation Review 142, no. : 102035.
An extended warranty is an additional service in the market that manufacturers and retailers provide for their customers. In this study, we investigate the optimal extended warranty strategies in a supply chain with a single manufacturer and a single retailer, and consider two single-channel models (the retailer solely provides the service, and the manufacturer solely provides the service) and a dual-channel model (both the retailer and the manufacturer provide the service). Using an analytical model, we demonstrate the optimal pricing decisions for the manufacturer and the retailer under these models and compare the profits of the manufacturer, retailer and supply chain. We find that among the models, customers enjoy a lower extended warranty price with a mild condition when the manufacturer provides the extended warranty service. However, the total profits of the supply chain are usually larger when the retailer sells the extended warranty. Through numerical experiments, we further investigate the influence of customer preferences, and find that the total profits of the supply chain increase if more customers purchase extended warranties from the retailer in the dual-channel model.
Lianmin Zhang; Lei Guan; Daniel Zhuoyu Long; Houcai Shen; Huajun Tang. Who is better off by selling extended warranties in the supply chain: the manufacturer, the retailer, or both? Annals of Operations Research 2020, 1 -27.
AMA StyleLianmin Zhang, Lei Guan, Daniel Zhuoyu Long, Houcai Shen, Huajun Tang. Who is better off by selling extended warranties in the supply chain: the manufacturer, the retailer, or both? Annals of Operations Research. 2020; ():1-27.
Chicago/Turabian StyleLianmin Zhang; Lei Guan; Daniel Zhuoyu Long; Houcai Shen; Huajun Tang. 2020. "Who is better off by selling extended warranties in the supply chain: the manufacturer, the retailer, or both?" Annals of Operations Research , no. : 1-27.
Blood shortage may lead to immeasurable losses. But the perishable nature of blood products limits the possibility of storing a large amount of it, and the quality of blood products reduces rapidly with transportation time. Specifically, in China, the management of blood products is even more complicated due to the significant demand for clinical blood, which increases every single year because of the reformation of the health system and the resulting scale expansion of hospitals. In this research, we aim to optimize the blood product scheduling scheme by constructing a vendor-managed inventory routing problem (VMIRP) for blood products, which balances the supply and demand such that the relevant operational cost is minimized. Then a decomposition-based algorithm is developed to solve the proposed mathematical model efficiently. Based on a series of numerical experiments of platelets, we obtain and examine the distribution plan and optimal transportation path over the planning horizon. In addition to the illustrated high algorithm efficiency, the computation results show that the VMIRP scheme can considerably decrease the operational cost of the blood supply chain.
Wenqian Liu; Ginger Y. Ke; Jian Chen; Lianmin Zhang. Scheduling the distribution of blood products: A vendor-managed inventory routing approach. Transportation Research Part E: Logistics and Transportation Review 2020, 140, 101964 .
AMA StyleWenqian Liu, Ginger Y. Ke, Jian Chen, Lianmin Zhang. Scheduling the distribution of blood products: A vendor-managed inventory routing approach. Transportation Research Part E: Logistics and Transportation Review. 2020; 140 ():101964.
Chicago/Turabian StyleWenqian Liu; Ginger Y. Ke; Jian Chen; Lianmin Zhang. 2020. "Scheduling the distribution of blood products: A vendor-managed inventory routing approach." Transportation Research Part E: Logistics and Transportation Review 140, no. : 101964.
We investigate a supply contract design problem in an assembly supply chain in which two heterogeneous suppliers produce complementary products and deliver them to the assembler. One supplier is more reliable and exhibits no supply risk, and the other is less reliable and exhibits supply risk. The assembler is better informed about demand and assembles these two types of components into final products. To elicit the assembler’s truthful report of private information, the more reliable supplier offers a contract to the assembler to determine the components’ quantities and the transfer payment. The less reliable supplier enduring a disruption designs a contract that includes the components’ quantities, the transfer payment and the unit penalty for any delivery shortfall. We study the cases where either supplier moves first and where they move simultaneously under symmetric and asymmetric demand information. We explore the values of the assembler’s information and find that the first mover is more reliant upon the existence of less asymmetric information and the second mover benefits more from the assembler’ information. Further, we find that a low reliability of the less reliable supplier enlarges the first mover’s value of information. We also examine the values of the contracting sequence and find that under symmetric information, the first mover benefits more from sequential contracting. However, interestingly, under asymmetric information, the first mover may benefit or be harmed by the first-mover right. We also find that a low reliability of the less reliable supplier discourages the supplier from using the first-mover right.
Yanfei Lan; Xiaoqiang Cai; Changjing Shang; Lianmin Zhang; Ruiqing Zhao. Heterogeneous suppliers’ contract design in assembly systems with asymmetric information. European Journal of Operational Research 2020, 286, 149 -163.
AMA StyleYanfei Lan, Xiaoqiang Cai, Changjing Shang, Lianmin Zhang, Ruiqing Zhao. Heterogeneous suppliers’ contract design in assembly systems with asymmetric information. European Journal of Operational Research. 2020; 286 (1):149-163.
Chicago/Turabian StyleYanfei Lan; Xiaoqiang Cai; Changjing Shang; Lianmin Zhang; Ruiqing Zhao. 2020. "Heterogeneous suppliers’ contract design in assembly systems with asymmetric information." European Journal of Operational Research 286, no. 1: 149-163.
We consider a problem in which a distributor purchases fresh products from multiple supply sources for subsequent sale at a wholesale market. Due to uncontrollable factors such as traffic congestion or bad weather conditions, the time taken for the product to be delivered from each production origin is uncertain. As the wholesale market is open for trading only in a fixed‐time window, any fresh products arriving earlier face the risk of decay, and any arriving later cannot be sold. The market demand for the product is random and follows a general distribution. We formulate the basic problem as a multi‐source selection model with random yield, taking into account the trade‐off between purchasing cost and other costs such as deterioration loss arising from delivery uncertainty. We derive the optimal order quantities from different origins and propose algorithms to search for them. We also investigate the effects of delivery uncertainty on service level and transport mode selection. Finally, we examine two extensions. One considers a capacity limit in each production origin, and the other incorporates information updating. For the first extension, we propose algorithms to compute the optimal solution based on its structural properties. For the second problem, we derive the optimal purchasing policy according to updated information such as details of the arrivals of previous orders.
Xiaolin Xu; Xiaoqiang Cai; Lianmin Zhang. Optimal Purchasing Policy for Fresh Products from Multiple Supply Sources with Considerations of Random Delivery Times, Risk, and Information. Decision Sciences 2020, 51, 1377 -1410.
AMA StyleXiaolin Xu, Xiaoqiang Cai, Lianmin Zhang. Optimal Purchasing Policy for Fresh Products from Multiple Supply Sources with Considerations of Random Delivery Times, Risk, and Information. Decision Sciences. 2020; 51 (6):1377-1410.
Chicago/Turabian StyleXiaolin Xu; Xiaoqiang Cai; Lianmin Zhang. 2020. "Optimal Purchasing Policy for Fresh Products from Multiple Supply Sources with Considerations of Random Delivery Times, Risk, and Information." Decision Sciences 51, no. 6: 1377-1410.
With a rigid requirement for environment protection, governments need to make appropriate policies to induce firms to adopt green technology in consideration of the rapidly increasing demand for environmentally friendly products. We investigated the government policy from the perspective of a supply chain, which consisted of the upstream government (she) and the downstream manufacturing firm (he). The government decided on the policy (tax or subsidy) to maximize the social welfare, while the firm decided on the greenness level of the product, which affects the consumers’ choice behavior and hence his own demand. Assuming else being equal, the government should adopt the tax policy if consumers are very sensitive to the greenness, the cost of greening is high, or the negative impact due to carbon emission is large, and subsidize the firm otherwise. We also conduct some numerical studies when price is endogenous. The main insights can be carried over.
Xing Yin; Xiaolin Chen; Xiaolin Xu; Lianmin Zhang. Tax or Subsidy? Optimal Carbon Emission Policy: A Supply Chain Perspective. Sustainability 2020, 12, 1548 .
AMA StyleXing Yin, Xiaolin Chen, Xiaolin Xu, Lianmin Zhang. Tax or Subsidy? Optimal Carbon Emission Policy: A Supply Chain Perspective. Sustainability. 2020; 12 (4):1548.
Chicago/Turabian StyleXing Yin; Xiaolin Chen; Xiaolin Xu; Lianmin Zhang. 2020. "Tax or Subsidy? Optimal Carbon Emission Policy: A Supply Chain Perspective." Sustainability 12, no. 4: 1548.
Reward-based crowdfunding is a new fund-raising method in sharing economy, and it can also be a powerful tool for companies to handle the time mismatch between money invested and revenue generated in Circular Economy (CE). While all-or-nothing (AON) mechanism and keep-it-all (KIA) mechanism are both used in crowdfunding projects, some websites start using a new hybrid mechanism where the creator can keep a proportion of the funds raised even if the crowdfunding project fails. In this paper, we investigate this hybrid mechanism in reward-based crowdfunding projects. For a basic two-stage model, we find that AON can provide the creator with the largest expected revenue under different pricing policies when the valuation of investors is discrete. However, with continuous investors’ valuation, a hybrid mechanism is better for the creator, and the price in the first stage should be lower than the one in the second stage. For a three-stage model, we find that the results with continuous valuation still hold, and a hybrid mechanism will be the optimal mechanism under menu pricing with discrete valuation.
Lei Guan; Yongxue Mu; Xiaolin Xu; Lianmin Zhang; Jun Zhuang. Keep it or give back? Optimal pricing strategy of reward-based crowdfunding with a hybrid mechanism in the sharing economy. International Journal of Production Research 2019, 58, 1 -22.
AMA StyleLei Guan, Yongxue Mu, Xiaolin Xu, Lianmin Zhang, Jun Zhuang. Keep it or give back? Optimal pricing strategy of reward-based crowdfunding with a hybrid mechanism in the sharing economy. International Journal of Production Research. 2019; 58 (22):1-22.
Chicago/Turabian StyleLei Guan; Yongxue Mu; Xiaolin Xu; Lianmin Zhang; Jun Zhuang. 2019. "Keep it or give back? Optimal pricing strategy of reward-based crowdfunding with a hybrid mechanism in the sharing economy." International Journal of Production Research 58, no. 22: 1-22.
We study the problem where independent operators of queueing systems cooperate to generate a win-win solution through capacity transfer among each other. We consider two types of costs: the congestion cost in the queueing system and the capacity transfer cost, and two types of queueing systems: M/M/1 and M/M/s. Service rates are considered to be capacities in M/M/1 and are assumed to be continuous, while numbers of servers are capacities in M/M/s.For the capacity transfer problem in M/M/1, we formulate it as a convex optimization problem and identify a cost sharing scheme which belongs to the core of the corresponding cooperative game. The special case with no transfer cost is also discussed. For the capacity transfer problem in M/M/s, we formulate it as a non-linear integer optimization problem, which we refer to as the server transfer problem. We first develop a marginal analysis algorithm to solve this problem when the unit transfer costs are equal among agents, and then propose a cost sharing rule which is shown to be in the core of the corresponding game. For the more general case with unequal unit transfer costs, we first show that the core of the corresponding game is non- empty. Then, we propose a greedy heuristic to find approximate solutions and design cost allocations rules for the corresponding game. Finally, we conduct numerical studies to evaluate the performance of the proposed greedy heuristic and the proposed cost allocation rules, and examine the value of capacity transferThis article is protected by copyright. All rights reserved.
Yinlian Zeng; Lianmin Zhang; Xiaoqiang Cai; Jun Li. Cost Sharing for Capacity Transfer in Cooperating Queueing Systems. Production and Operations Management 2017, 27, 644 -662.
AMA StyleYinlian Zeng, Lianmin Zhang, Xiaoqiang Cai, Jun Li. Cost Sharing for Capacity Transfer in Cooperating Queueing Systems. Production and Operations Management. 2017; 27 (4):644-662.
Chicago/Turabian StyleYinlian Zeng; Lianmin Zhang; Xiaoqiang Cai; Jun Li. 2017. "Cost Sharing for Capacity Transfer in Cooperating Queueing Systems." Production and Operations Management 27, no. 4: 644-662.
In this paper, we propose a higher-order interactive hidden Markov model, which incorporates both the feedback effects of observable states on hidden states and their mutual long-term dependence. The key idea of this model is to assume the probability laws governing both the observable and hidden states can be written as a pair of higher-order stochastic difference equations. We also present an efficient procedure, a heuristic algorithm, to estimate the hidden states of the chain and the model parameters. Real applications in SSE Composite Index data and default data are given to demonstrate the effectiveness of our proposed model and corresponding estimation method.
Dong-Mei Zhu; Wai-Ki Ching; Robert J. Elliott; Tak-Kuen Siu; Lianmin Zhang. A Higher-order interactive hidden Markov model and its applications. OR Spectrum 2017, 39, 1055 -1069.
AMA StyleDong-Mei Zhu, Wai-Ki Ching, Robert J. Elliott, Tak-Kuen Siu, Lianmin Zhang. A Higher-order interactive hidden Markov model and its applications. OR Spectrum. 2017; 39 (4):1055-1069.
Chicago/Turabian StyleDong-Mei Zhu; Wai-Ki Ching; Robert J. Elliott; Tak-Kuen Siu; Lianmin Zhang. 2017. "A Higher-order interactive hidden Markov model and its applications." OR Spectrum 39, no. 4: 1055-1069.
Dong-Mei Zhu; Wai-Ki Ching; Robert J. Elliott; Tak-Kuen Siu; Lianmin Zhang. Hidden Markov models with threshold effects and their applications to oil price forecasting. Journal of Industrial & Management Optimization 2017, 13, 757 -773.
AMA StyleDong-Mei Zhu, Wai-Ki Ching, Robert J. Elliott, Tak-Kuen Siu, Lianmin Zhang. Hidden Markov models with threshold effects and their applications to oil price forecasting. Journal of Industrial & Management Optimization. 2017; 13 (2):757-773.
Chicago/Turabian StyleDong-Mei Zhu; Wai-Ki Ching; Robert J. Elliott; Tak-Kuen Siu; Lianmin Zhang. 2017. "Hidden Markov models with threshold effects and their applications to oil price forecasting." Journal of Industrial & Management Optimization 13, no. 2: 757-773.
Y.J. Xiao; Y.H. Kuo; Y. Zheng; L.M. Zhang. A combined zone-LP and simulated annealing algorithm for unequal-area facility layout problem. Advances in Production Engineering & Management 2016, 11, 259 -270.
AMA StyleY.J. Xiao, Y.H. Kuo, Y. Zheng, L.M. Zhang. A combined zone-LP and simulated annealing algorithm for unequal-area facility layout problem. Advances in Production Engineering & Management. 2016; 11 (4):259-270.
Chicago/Turabian StyleY.J. Xiao; Y.H. Kuo; Y. Zheng; L.M. Zhang. 2016. "A combined zone-LP and simulated annealing algorithm for unequal-area facility layout problem." Advances in Production Engineering & Management 11, no. 4: 259-270.
In this paper, we consider a two-echelon sustainable supply chain with price-sensitive demand. The government taxes the carbon footprint of each item caused by producing, transporting, and consuming the products. Both the supplier and retailer can exert efforts to reduce the carbon footprint. In a non-cooperative setting, the government only taxes the supplier, so that the retailer has no incentive to exert any effort to reduce the carbon footprint and the supplier merely decides on the selling price to maximize its own profit. We develop a centralized supply chain and show that there is an optimal solution to maximize the channel profit. Since the centralized policy may not be always not practical, we propose a tax-sharing contract, where both parties profit from the carbon footprint reduction. This problem is modeled as the Stackelberg game and Nash game. The results show that the leader has more power than the follower, which results in more profit. The Stackelberg game provides boundaries for both parties’ profits in the Nash game. Although the tax-sharing contract does not result in full cooperation, its efficiency is still much higher than that of the non-cooperative case. The results are illustrated with some numerical experiments.
Yujie Xiao; Shuai Yang; Lianmin Zhang; Yong-Hong Kuo. Supply Chain Cooperation with Price-Sensitive Demand and Environmental Impacts. Sustainability 2016, 8, 716 .
AMA StyleYujie Xiao, Shuai Yang, Lianmin Zhang, Yong-Hong Kuo. Supply Chain Cooperation with Price-Sensitive Demand and Environmental Impacts. Sustainability. 2016; 8 (8):716.
Chicago/Turabian StyleYujie Xiao; Shuai Yang; Lianmin Zhang; Yong-Hong Kuo. 2016. "Supply Chain Cooperation with Price-Sensitive Demand and Environmental Impacts." Sustainability 8, no. 8: 716.
When the spatial location area increases becoming extremely large, it is very difficult, if not possible, to evaluate the covariance matrix determined by the set of location distance even for gridded stationary Gaussian process. To alleviate the numerical challenges, we construct a nonparametric estimator called periodogram of spatial version to represent the sample property in frequency domain, because periodogram requires less computational operation by fast Fourier transform algorithm. Under some regularity conditions on the process, we investigate the asymptotic unbiasedness property of periodogram as estimator of the spectral density function and achieve the convergence rate.
Kun Chen; Lianmin Zhang; Maolin Pan. Spectral Methods in Spatial Statistics. Discrete Dynamics in Nature and Society 2014, 2014, 1 -6.
AMA StyleKun Chen, Lianmin Zhang, Maolin Pan. Spectral Methods in Spatial Statistics. Discrete Dynamics in Nature and Society. 2014; 2014 ():1-6.
Chicago/Turabian StyleKun Chen; Lianmin Zhang; Maolin Pan. 2014. "Spectral Methods in Spatial Statistics." Discrete Dynamics in Nature and Society 2014, no. : 1-6.