Joint Inventory and Pricing Coordination with Incomplete Demand Information

Lu, Ye; Song, Miao; Yang, Yi

doi:10.1111/poms.12504

Cited by 16 publications

(28 citation statements)

References 28 publications

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“…Remark As K ‐approximation convexity can be preserved by expectation (proposition 1 in Lu et al. ), Theorem also holds for the CTGEA approach.…”

Section: Optimality Analysis and Heuristic Policiesmentioning

confidence: 91%

“…In Step 3, we extend the convex envelope of W(x) from the domain (x 1 , x mÀ1 ) to the domain (À∞, +∞). Lu et al (2016) proposed a linear programming formulation to obtain the convex approximation of a continuous piecewise linear function W(x). However, the cost function defined by Equation (1) in this study may not be continuous, in which case it cannot be approximated by solving the linear programming formulation but can be approximated by using Algorithm 1.…”

Section: Algorithm 1 Obtain a Convex Approximationmentioning

confidence: 99%

“…This observation confirms that the expectation under some demand distributions may smooth the objective function in the sense that the gap with the convex approximation function becomes smaller. Proposition 1 in Lu et al (2016) showed that if f(x) is K-approximate convex, then E[f (x À D)] is K-approximate convex for any random variable D. Therefore, smoothing by expectation at least does not make the function become non-convex if it does not make the function more convex.…”

Section: Cost-to-go Function Expectationmentioning

confidence: 99%

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Approximation Approaches for Inventory Systems with General Production/Ordering Cost Structures

Song

Yang

2018

Production and Operations Management

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The production/ordering cost structure is fundamental to determining an optimal inventory control policy. For example, it is well known that a base‐stock policy is optimal for inventory systems with linear production costs, whereas an (s, S) policy is optimal if both linear and fixed costs exist. However, many of the cost structures that have arisen from the practice are quite complex and make the optimal policies too complicated for managers to implement. In this study, we propose several easy‐to‐implement and efficient heuristic policies for inventory systems with general production costs, which include multiple linear pieces and fixed costs, suggesting a wide application to many practical problems that were previously difficult to solve. We establish the worst‐case performance bounds on the proposed heuristic policies by using the concept of K‐approximate convexity. Our extensive numerical studies, which are designed to reflect practical inventory control applications, evaluate the performance of the heuristic policies and show that the best heuristic policy we propose performs extremely well. We also try to provide explanations for the performance of different heuristic policies.

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“…Remark As K ‐approximation convexity can be preserved by expectation (proposition 1 in Lu et al. ), Theorem also holds for the CTGEA approach.…”

Section: Optimality Analysis and Heuristic Policiesmentioning

confidence: 91%

Section: Algorithm 1 Obtain a Convex Approximationmentioning

confidence: 99%

Section: Cost-to-go Function Expectationmentioning

confidence: 99%

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Approximation Approaches for Inventory Systems with General Production/Ordering Cost Structures

Song

Yang

2018

Production and Operations Management

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“…Lu and Song [15] characterized the optimal policies for single-period and multi-period inventory systems, respectively, where the production cost includes a fixed cost and a piecewise linear convex variable cost. Lu et al [16] put forward a new approach called K-approximate convexity to study the multi-period joint pricing and inventory control problem with incomplete demand information and a nonconcave revenue function. Feinberg and Liang [9] explored the structure of the optimal inventory policies for a multi-period inventory control system with fixed ordering costs and all possible values of discount factor under both finite and infinite horizons.…”

Section: Literature Reviewmentioning

confidence: 99%

Impacts of put option contract and supply chain structure in a multi-period supply chain with uncertain demand

Wan

Fan

2021

RAIRO-Oper. Res.

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This paper builds the multi-period optimization models that incorporate put option contract and two supply chain structures to determine the production decision for a supplier and the ordering decision for a manufacturer in a two-stage supply chain. This paper applies the method of dynamic programming to derive the structures of optimal policies and provides an approximate algorithm to evaluate the myopic policies. This paper also conducts numerical examples to illustrate the impacts of put option contract, supply chain structure and demand risk on the members’ decisions and total profits as well as the channel’s total profit. The results indicate that put option contract can motivate to increase the channel’s service level and reduce the manufacturer’s inventory risk under two supply chain structures, when compared to the case without put option contract. In the manufacturer-led structure, the channel always benefits from put option contract, the supplier benefits from put option contract with a high option price and a low exercise price, while the manufacturer benefits from put option contract with a low option price and a high exercise price. In the supplier-led structure, the channel and the manufacturer always benefit from put option contract, while the supplier benefits from put option contract with a high option price and a low exercise price. With put option contract, the supplier is more profitable in the manufacturer-led structure than in the supplier-led structure, while the manufacturer and the channel are more profitable in the supplier-led structure than in the manufacturer-led structure. Without and with put option contract, the optimal total profits of two members and the channel will first decrease and then increase in the demand risk. Finally, this paper identifies the explicit conditions under which the multi-period supply chain can be coordinated via put option contract under two supply chain structures. With a coordinating contract, the supplier and the manufacturer are better off compared to the case without put option contract.

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“…Aydin and Porteus (2008) considered the model similar to Dada and Petruzzi's (1999) with an additional scope to include multiple products in a given assortment, under price-based substitution. Lu et al (2016) developed the K-approximate convexity, to solve this inventory-pricing coordination problems and to provide well-structured heuristic policies.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

An Optimal Model at the Interface of Operations with Social Media Marketing

Teyarachakul

2018

OSCM: An Int. Journal

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Social media sales and the logistics of products is being shuttled into a new technological paradigm. The purpose of this paper is to review the role of social media sales force and its effects on lot size process and the pricing under an infinite-time horizon assumption. We begin with reviewing the role and importance of social media in business; with a focus on the mathematic deterministic model for decision making that offer ways in which social media influences each step. Scenarios are specifically considered. In the first scenario, price is determined by the market. What size to hold inventoried products and what to budget for promotions on a social media platform are the important variables in market determined pricing. In the second scenario, price is examined by the decision maker based on maximizing the profit margin. In this first case scenario, advertising and product prices are jointly considered to maximize the profit margin. In this second case scenario, lot sizing is considered to minimize costs of holding inventories and placing orders. In both scenarios, the profit function outcome is concave. Therefore, the model optimizes solutions for pricing, lot-sizing for social media advertising policies.

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Joint Inventory and Pricing Coordination with Incomplete Demand Information

Cited by 16 publications

References 28 publications

Approximation Approaches for Inventory Systems with General Production/Ordering Cost Structures

Approximation Approaches for Inventory Systems with General Production/Ordering Cost Structures

Impacts of put option contract and supply chain structure in a multi-period supply chain with uncertain demand

An Optimal Model at the Interface of Operations with Social Media Marketing

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