scholarly journals A New Proof for the Tight Range of Optimal Order Quantities for the Newsboy Problem with Mean and Standard Deviation

2012 ◽  
Vol 02 (02) ◽  
pp. 203-206 ◽  
Author(s):  
Jinfeng Yue
Keyword(s):  
Standard Deviation ◽  
Optimal Order ◽  
Newsboy Problem ◽  
Order Quantities

scholarly journals One-Way Substitution Newsboy Problem under Retailer’s Budget Constraint

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
L. L. Zhang ◽  
Y. Yang ◽  
J. Q. Cai
Keyword(s):  
Economic Activity ◽  
Practical Problem ◽  
Numerical Study ◽  
Budget Constraint ◽  
Optimal Order ◽  
Optimal Solutions ◽  
Newsboy Problem ◽  
Optimal Decisions ◽  
Order Quantities ◽  
Demand Scenario

One-way substitution means that when low-end brand goods are sold out, high-end brand goods can be offered to consumers as substitute goods, but not the opposite. In realistic economic activity, “shortage of funds” is a common practical problem for the retailer in making order decision. This paper proposes a nonlinear optimization model with the retailer’s budget to study the optimal order quantities and substitution discount for two one-way substitution products under a stochastic demand scenario, and the objective is to maximize the retailer’s revenue. We solve the model mainly according to the Karush–Kuhn–Tucker (KKT) theorem and present the conditions of optimal decisions. Finally, through the numerical study, we analyze the influence of the budget constraint and other parameters on the optimal solutions.

Supplies from developing countries: Optimal order quantities under loss risks

Omega ◽  
2008 ◽  
Vol 36 (1) ◽  
pp. 122-130 ◽  
Author(s):  
Jayavel Sounderpandian ◽  
Sameer Prasad ◽  
Manu Madan
Keyword(s):  
Developing Countries ◽  
Optimal Order ◽  
Order Quantities

Coordination Policies for Multi-Echelon Multi-Product Inventory Systems

2011 ◽  
pp. 153-163
Author(s):  
Fidel Torres ◽  
Gonzalo Mejía
Keyword(s):  
Mathematical Model ◽  
Inventory Systems ◽  
Optimal Order ◽  
Distribution Centers ◽  
Operational Costs ◽  
Production Distribution ◽  
Replenishment Policy ◽  
Order Quantities ◽  
Product Inventory ◽  
Coordination And Collaboration

The effective coordination is a key element in the success of many cooperative supply chains. All production, distribution and supply must be adequately synchronized in order to satisfy the customer needs and at the same time optimizing the operational costs. This paper presents a multi-product, multi-echelon inventory system which comprises one manufacturer, a number of distribution centers and a number of retailers which are dependent of such distribution centers. The coordination and collaboration is achieved through a carefully designed replenishment policy. The near-optimal order quantities for each of the supply chain agents are calculated with a mathematical model in which the integrality constraints are relaxed. A number of instances were generated and tested. The results show the validity of the proposed approach.

scholarly journals A Two-Period Newsvendor Model with Product Extension and Shortage-Making Strategy

2013 ◽  
Vol 2013 ◽  
pp. 1-4
Author(s):  
Kuo-Hsien Wang ◽  
Che-Tsung Tung ◽  
Yuan-Chih Huang
Keyword(s):  
Optimal Order ◽  
Ripple Effect ◽  
Newsvendor Model ◽  
Numerical Examples ◽  
Deterministic Demand ◽  
Proposed Model ◽  
Demand Rate ◽  
Order Quantities ◽  
Second Period ◽  
Product Extension

This study deals with a two-period newsvendor setting in which the item in the second period is a product extension of the item in the first period. A shortage strategy toward the first item is intentionally made so as to stimulate more sales amounts of the second item. The stochastic demand of these two items is assumed to be a linear-additive pattern comprising a deterministic demand and an error demand, where the deterministic demand consists of a primary demand and a consumer price elasticity, and the error demand is hypothesized to be exponentially distributed. The objective of this study is to optimize system's overall expected profit by jointly determining the optimal order quantities and selling prices of these two items. We first compare our proposed model with the classical newsvendor model in light of profit performances, and it reveals that a higher shifting demand rate makes our model a more profitable setting. Impact on profit performances caused by an increasing primary demand of the second item is then demonstrated by numerical examples that an unthought-of ripple effect of an increasing error demand of the second item also occurs.

scholarly journals Opportunity Loss Minimization and Newsvendor Behavior

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Xinsheng Xu ◽  
Hong Yan ◽  
Chi Kin Chan
Keyword(s):  
Conditional Value At Risk ◽  
Optimal Order ◽  
Market Demand ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Loss Minimization ◽  
Decision Bias ◽  
Optimal Order Quantity ◽  
Opportunity Loss ◽  
Order Quantities

To study the decision bias in newsvendor behavior, this paper introduces an opportunity loss minimization criterion into the newsvendor model with backordering. We apply the Conditional Value-at-Risk (CVaR) measure to hedge against the potential risks from newsvendor’s order decision. We obtain the optimal order quantities for a newsvendor to minimize the expected opportunity loss and CVaR of opportunity loss. It is proven that the newsvendor’s optimal order quantity is related to the density function of market demand when the newsvendor exhibits risk-averse preference, which is inconsistent with the results in Schweitzer and Cachon (2000). The numerical example shows that the optimal order quantity that minimizes CVaR of opportunity loss is bigger than expected profit maximization (EPM) order quantity for high-profit products and smaller than EPM order quantity for low-profit products, which is different from the experimental results in Schweitzer and Cachon (2000). A sensitivity analysis of changing the operation parameters of the two optimal order quantities is discussed. Our results confirm that high return implies high risk, while low risk comes with low return. Based on the results, some managerial insights are suggested for the risk management of the newsvendor model with backordering.

scholarly journals Pre-sale ordering strategy based on the new retail context considering bounded consumer rationality

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Yu Liu ◽  
Chun-xiang Guo ◽  
Hong Zhou ◽  
Xin-yi Chen
Keyword(s):  
Reference Price ◽  
Value Added ◽  
Purchase Behavior ◽  
Optimal Order ◽  
Order Quantity ◽  
The Public ◽  
Optimal Value ◽  
Public Policymaker ◽  
Order Quantities ◽  
The Impact

<p style='text-indent:20px;'>The purpose of this paper is to study the impact of bounded consumer rationality on the order quantity and profitability of the seller in the advance period and the spot period in the context of the combination of new retail and pre-sale. In this paper, we develop a seller order model in the context of the combination of new retail and pre-sale, with and without reference price dependence. Besides, the model considers the order cancellation and delayed purchase behavior of consumers. We then discuss the optimal profit and optimal order quantity under different conditions and the effect of different reference price dependence and value-added offline service on them. Our research shows that: First, the seller tends to set the deposit too low in pre-sales. Second, reference price dependence has different effects on order quantities in different periods. The seller should pay more attention to the impact of reference price dependence. Third, on the whole, consumer rationality benefits the seller. The seller, or the public policymaker, can benefit new retail businesses by increasing consumer rationality. Last, in the new retail context, an increase in offline service value-added, even if it increases total order quantity, is not always beneficial to the seller and may reduce profits. Therefore, the seller should weigh all factors to determine the optimal value-added offline services.</p>

scholarly journals Intelligent Traffic Signal Phase Distribution System Using Deep Q-Network

2022 ◽  
Vol 12 (1) ◽  
pp. 425
Author(s):  
Hyunjin Joo ◽  
Yujin Lim
Keyword(s):  
Control System ◽  
Standard Deviation ◽  
Traffic Congestion ◽  
Queue Length ◽  
Smart Cities ◽  
Traffic Signal ◽  
Optimal Order ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Smart Transportation

Traffic congestion is a worsening problem owing to an increase in traffic volume. Traffic congestion increases the driving time and wastes fuel, generating large amounts of fumes and accelerating environmental pollution. Therefore, traffic congestion is an important problem that needs to be addressed. Smart transportation systems manage various traffic problems by utilizing the infrastructure and networks available in smart cities. The traffic signal control system used in smart transportation analyzes and controls traffic flow in real time. Thus, traffic congestion can be effectively alleviated. We conducted preliminary experiments to analyze the effects of throughput, queue length, and waiting time on the system performance according to the signal allocation techniques. Based on the results of the preliminary experiment, the standard deviation of the queue length is interpreted as an important factor in an order allocation technique. A smart traffic signal control system using a deep Q-network , which is a type of reinforcement learning, is proposed. The proposed algorithm determines the optimal order of a green signal. The goal of the proposed algorithm is to maximize the throughput and efficiently distribute the signals by considering the throughput and standard deviation of the queue length as reward parameters.

scholarly journals Loss-Averse Retailer’s Optimal Ordering Policies for Perishable Products with Customer Returns

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Xu Chen ◽  
Qian Zhou
Keyword(s):  
Optimal Order ◽  
Order Quantity ◽  
Policy Model ◽  
Decision Bias ◽  
Perishable Product ◽  
Ordering Policy ◽  
Optimal Order Quantity ◽  
Ordering Policies ◽  
Customer Returns ◽  
Order Quantities

We investigate the loss-averse retailer’s ordering policies for perishable product with customer returns. With the introduction of the segmental loss utility function, we depict the retailer’s loss aversion decision bias and establish the loss-averse retailer’s ordering policy model. We derive that the loss-averse retailer’s optimal order quantity with customer returns exists and is unique. By comparison, we obtain that both the risk-neutral and the loss-averse retailer’s optimal order quantities depend on the inventory holding cost and the marginal shortage cost. Through the sensitivity analysis, we also discuss the effect of loss-averse coefficient and the ratio of return on the loss-averse retailer’s optimal order quantity with customer returns.

Sign in / Sign up

Export Citation Format

Share Document