Allocation planning in sales hierarchies with stochastic demand and service-level targets

OR Spectrum ◽  
2018 ◽  
Vol 41 (4) ◽  
pp. 981-1024 ◽  
Author(s):  
Konstantin Kloos ◽  
Richard Pibernik ◽  
Benedikt Schulte
Keyword(s):  
Stochastic Demand ◽  
Service Level ◽  
Allocation Planning

Allocation planning under service-level contracts

2020 ◽  
Vol 280 (1) ◽  
pp. 203-218 ◽  
Author(s):  
Konstantin Kloos ◽  
Richard Pibernik
Keyword(s):  
Service Level ◽  
Allocation Planning

scholarly journals Complexity Dynamic Character Analysis of Retailers Based on the Share of Stochastic Demand and Service

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12
Author(s):  
Junhai Ma ◽  
Weiya Di ◽  
Hao Ren
Keyword(s):  
Stochastic Demand ◽  
Stable State ◽  
Service Level ◽  
Price Adjustment ◽  
Stable Region ◽  
Largest Lyapunov Exponent ◽  
Market Demand ◽  
Price Fluctuation ◽  
Adjustment Speed ◽  
The Stability

Apart from the price fluctuation, the retailers’ service level becomes another key factor that affects the market demand. This paper depicts a modified price and demand game model based on the stochastic demand and the retailer’s service level which influences the market demand decided by customers’ preference, while the market demand is stochastic in this model. We explore how the price adjustment speed affects the stability of the supply chain system with respect to service level and stochastic demand. The dynamic behavior of the system is researched by simulation and the stability domain and the bifurcation phenomenon are shown clearly. The largest Lyapunov exponent and the chaotic attractor are also given to confirm the chaotic characteristic of the system. The simulation results indicate that relatively small price adjustment speed may maintain the system at stable state. With the price adjustment speed gradually increasing, the price system gets unstable and finally becomes chaotic. This chaotic phenomenon will perturb the product market and this phenomenon should be controlled to keep the system stay in the stable region. So the chaos control is done and the chaos can be controlled completely. The conclusion makes significant contribution to the system referring to the price fluctuation based on the service level and stochastic demand.

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.

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