scholarly journals A nonlinear optimization model for optimal order quantities with stochastic demand rate and price change

2007 ◽  
Vol 3 (1) ◽  
pp. 139-154 ◽  
Author(s):  
M. M. Ali ◽  
◽  
L. Masinga
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Model ◽  
Price Change ◽  
Stochastic Demand ◽  
Optimal Order ◽  
Demand Rate ◽  
Order Quantities

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.

Optimal multi-product supplier selection under stochastic demand with service level and budget constraints using learning vector quantization neural network

2019 ◽  
Vol 53 (5) ◽  
pp. 1709-1720
Author(s):  
Hajar HormozzadehGhalati ◽  
Alireza Abbasi ◽  
Abolghasem Sadeghi-Niaraki
Keyword(s):  
Neural Network ◽  
Vector Quantization ◽  
Supplier Selection ◽  
Stochastic Demand ◽  
Service Level ◽  
Learning Vector Quantization ◽  
Optimal Number ◽  
Optimal Order ◽  
Budget Constraints ◽  
Order Quantities

In today’s competitive marketplace demand, evaluation and selection of suppliers are pivotal for firms, and therefore decision makers need to select suppliers and the optimal order quantities when outsourcing. However, there is uncertainty and risk due to lack of precise data for supplier selection. Uncertainty can impose shortage or overstocks, because of stochastic demand, to firms; in this case, considering inventory control is essential. In this research, an appropriate spatial model is developed for a multi-product supplier selection model with service level and budget constraints. Learning Vector Quantization Neural Network is used to find the optimal number of decision variables with the goal of maximizing the expected profit of supply chains. By analyzing a practical example and conducting sensitivity analysis, we find that corporate profit will be maximized if the optimal integration of suppliers and the optimal order quantities from each supplier is determined. In addition, budget and service level should be considered in the process of finding the best result.

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

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.

Mixed-integer nonlinear optimization for district heating network expansion

2020 ◽  
Vol 68 (12) ◽  
pp. 985-1000
Author(s):  
Marius Roland ◽  
Martin Schmidt
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Model ◽  
Thermal Effects ◽  
Nonlinear Models ◽  
Valid Inequalities ◽  
Average Power ◽  
District Heating ◽  
Mixed Integer ◽  
Mixed Integer Nonlinear Optimization

AbstractWe present a mixed-integer nonlinear optimization model for computing the optimal expansion of an existing tree-shaped district heating network given a number of potential new consumers. To this end, we state a stationary and nonlinear model of all hydraulic and thermal effects in the pipeline network as well as nonlinear models for consumers and the network’s depot. For the former, we consider the Euler momentum and the thermal energy equation. The thermal aspects are especially challenging. Here, we develop a novel polynomial approximation that we use in the optimization model. The expansion decisions are modeled by binary variables for which we derive additional valid inequalities that greatly help to solve the highly challenging problem. Finally, we present a case study in which we identify three major aspects that strongly influence investment decisions: the estimated average power demand of potentially new consumers, the distance between the existing network and the new consumers, and thermal losses in the network.

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