Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random Demands
Vendor managed inventory (VMI) is an improved sustainable inventory management system, but it is difficult to establish and solve an integrated Stackelberg game model under the complicated practical environment. In this paper, a bilevel programming model is proposed to formulate the VMI system by ta...
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doaj-18b975e01dd84571ade535a161e018482020-11-25T02:40:35ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/36874713687471Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random DemandsHua Deng0Yinxue Li1Zhaoman Wan2Zhong Wan3School of Mathematics and Statistics, Central South University, Changsha, ChinaSchool of Mathematics and Statistics, Central South University, Changsha, ChinaSchool of Mathematics and Statistics, Central South University, Changsha, ChinaSchool of Mathematics and Statistics, Central South University, Changsha, ChinaVendor managed inventory (VMI) is an improved sustainable inventory management system, but it is difficult to establish and solve an integrated Stackelberg game model under the complicated practical environment. In this paper, a bilevel programming model is proposed to formulate the VMI system by taking into account the uncertainty of demand, the competition among retailers, the cooperative advertising, the shortage and holding costs, and the practical constraints. For the established stochastic model being associated with continuously random demands, a deterministic mathematical program with complementarity constraints (MPCC) is first derived by expectation method and the first-order optimality conditions of the lower-level problem. Then, with a partially smoothing technique, the MPCC is solved by transforming it into a series of standard smooth optimization subproblems. Finally, owing to complexity caused by evaluating the integrals with unknown decision variables in the objective function, an efficient algorithm is developed to solve the problem based on the gradient information of model. Sensitivity analysis has been employed to reveal a number of managerial implications from the constructed model and algorithm. (1) The participation rate depends on advertising expenditures from both the manufacturer and the retailer. There exists an optimal threshold of participation rate for the manufacturer, which can be provided by the intersection point of the manufacturer and retailer’s cost-profit curves. (2) The manufacturer’s advertising policy is less sensitive to uncertainty of demand than the change of the retailer’s advertising policy. (3) The manufacturer in the VMI system should concern about the differences caused by symmetric or asymmetric retailers.http://dx.doi.org/10.1155/2020/3687471 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hua Deng Yinxue Li Zhaoman Wan Zhong Wan |
spellingShingle |
Hua Deng Yinxue Li Zhaoman Wan Zhong Wan Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random Demands Mathematical Problems in Engineering |
author_facet |
Hua Deng Yinxue Li Zhaoman Wan Zhong Wan |
author_sort |
Hua Deng |
title |
Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random Demands |
title_short |
Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random Demands |
title_full |
Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random Demands |
title_fullStr |
Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random Demands |
title_full_unstemmed |
Partially Smoothing and Gradient-Based Algorithm for Optimizing the VMI System with Competitive Retailers under Random Demands |
title_sort |
partially smoothing and gradient-based algorithm for optimizing the vmi system with competitive retailers under random demands |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2020-01-01 |
description |
Vendor managed inventory (VMI) is an improved sustainable inventory management system, but it is difficult to establish and solve an integrated Stackelberg game model under the complicated practical environment. In this paper, a bilevel programming model is proposed to formulate the VMI system by taking into account the uncertainty of demand, the competition among retailers, the cooperative advertising, the shortage and holding costs, and the practical constraints. For the established stochastic model being associated with continuously random demands, a deterministic mathematical program with complementarity constraints (MPCC) is first derived by expectation method and the first-order optimality conditions of the lower-level problem. Then, with a partially smoothing technique, the MPCC is solved by transforming it into a series of standard smooth optimization subproblems. Finally, owing to complexity caused by evaluating the integrals with unknown decision variables in the objective function, an efficient algorithm is developed to solve the problem based on the gradient information of model. Sensitivity analysis has been employed to reveal a number of managerial implications from the constructed model and algorithm. (1) The participation rate depends on advertising expenditures from both the manufacturer and the retailer. There exists an optimal threshold of participation rate for the manufacturer, which can be provided by the intersection point of the manufacturer and retailer’s cost-profit curves. (2) The manufacturer’s advertising policy is less sensitive to uncertainty of demand than the change of the retailer’s advertising policy. (3) The manufacturer in the VMI system should concern about the differences caused by symmetric or asymmetric retailers. |
url |
http://dx.doi.org/10.1155/2020/3687471 |
work_keys_str_mv |
AT huadeng partiallysmoothingandgradientbasedalgorithmforoptimizingthevmisystemwithcompetitiveretailersunderrandomdemands AT yinxueli partiallysmoothingandgradientbasedalgorithmforoptimizingthevmisystemwithcompetitiveretailersunderrandomdemands AT zhaomanwan partiallysmoothingandgradientbasedalgorithmforoptimizingthevmisystemwithcompetitiveretailersunderrandomdemands AT zhongwan partiallysmoothingandgradientbasedalgorithmforoptimizingthevmisystemwithcompetitiveretailersunderrandomdemands |
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