scholarly journals An Optimal Decision Model of Production-Inventory with MTS and ATO Hybrid Model Considering Uncertain Demand

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Dezhi Zhang ◽  
Xialian Li ◽  
Xiamiao Li ◽  
Shuangyan Li ◽  
Qi Qian
Keyword(s):  
Production System ◽  
Decision Model ◽  
Demand Uncertainty ◽  
Demand Forecasting ◽  
Uncertain Demand ◽  
Optimal Decision ◽  
Inventory Level ◽  
Demand Information ◽  
Make To Stock ◽  
Inventory Decision

This paper presents an optimization decision model for a production system that comprises the hybrid make-to-stock/assemble-to-order (MTS/ATO) organization mode with demand uncertainty, which can be described as a two-stage decision model. In the first decision stage (i.e., before acquiring the actual demand information of the customer), we have studied the optimal quantities of the finished products and components, while in the second stage (i.e., after acquiring the actual demand information of the customer), we have made the optimal decision on the assignment of components to satisfy the remaining demand. The optimal conditions on production and inventory decision are deduced, as well as the bounds of the total procurement quantity of the components in the ATO phase and final products generated in the MTS phase. Finally, an example is given to illustrate the above optimal model. The findings are shown as follows: the hybrid MTS and ATO production system reduces uncertain demand risk by arranging MTS phase and ATO phase reasonably and improves the expected profit of manufacturer; applying the strategy of component commonality can reduce the total inventory level, as well as the risk induced by the lower accurate demand forecasting.

The Pulse of Urban Transport: Exploring the Co-evolving Pattern for Spatio-temporal Forecasting

2021 ◽  
Vol 15 (6) ◽  
pp. 1-25
Author(s):  
Jinliang Deng ◽  
Xiusi Chen ◽  
Zipei Fan ◽  
Renhe Jiang ◽  
Xuan Song ◽  
...  
Keyword(s):  
Time Series Data ◽  
Demand Forecasting ◽  
Intrinsic Property ◽  
Urban Transport ◽  
Series Data ◽  
Transportation Demand ◽  
Demand Information ◽  
Spatio Temporal ◽  
Mode Of Transport ◽  
Pattern Information

Transportation demand forecasting is a topic of large practical value. However, the model that fits the demand of one transportation by only considering the historical data of its own could be vulnerable since random fluctuations could easily impact the modeling. On the other hand, common factors like time and region attribute, drive the evolution demand of different transportation, leading to a co-evolving intrinsic property between different kinds of transportation. In this work, we focus on exploring the co-evolution between different modes of transport, e.g., taxi demand and shared-bike demand. Two significant challenges impede the discovery of the co-evolving pattern: (1) diversity of the co-evolving correlation, which varies from region to region and time to time. (2) Multi-modal data fusion. Taxi demand and shared-bike demand are time-series data, which have different representations with the external factors. Moreover, the distribution of taxi demand and bike demand are not identical. To overcome these challenges, we propose a novel method, known as co-evolving spatial temporal neural network (CEST). CEST learns a multi-view demand representation for each mode of transport, extracts the co-evolving pattern, then predicts the demand for the target transportation based on multi-scale representation, which includes fine-scale demand information and coarse-scale pattern information. We conduct extensive experiments to validate the superiority of our model over the state-of-art models.

On the Equilibrium Uniqueness in Cournot Competition with Demand Uncertainty

2020 ◽  
Vol 20 (2) ◽  
Author(s):  
Stefanos Leonardos ◽  
Costis Melolidakis
Keyword(s):  
Failure Rate ◽  
Demand Uncertainty ◽  
Sufficient Conditions ◽  
Cournot Competition ◽  
Uncertain Demand ◽  
Cournot Model ◽  
Equilibrium Uniqueness ◽  
Residual Demand ◽  
Uniqueness Of Equilibrium ◽  
Additional Assumptions

AbstractWe revisit the linear Cournot model with uncertain demand that is studied in Lagerlöf (2006. “Equilibrium Uniqueness in a Cournot Model with Demand Uncertainty.” The B.E. Journal of Theoretical Economics 6, no. 1. (Topics), Article 19: 1–6.) and provide sufficient conditions for equilibrium uniqueness that complement the existing results. We show that if the distribution of the demand intercept has the decreasing mean residual demand (DMRD) or the increasing generalized failure rate (IGFR) property, then uniqueness of equilibrium is guaranteed. The DMRD condition implies log-concavity of the expected profits per unit of output without additional assumptions on the existence or the shape of the density of the demand intercept and, hence, answers in the affirmative the conjecture of Lagerlöf (2006. “Equilibrium Uniqueness in a Cournot Model with Demand Uncertainty.” The B.E. Journal of Theoretical Economics 6, no. 1. (Topics), Article 19: 1–6.) that such conditions may not be necessary.

scholarly journals Optimal Decision-Making to Charge Electric Vehicles in Heterogeneous Networks: Stackelberg Game Approach

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 325 ◽  
Author(s):  
Shijun Chen ◽  
Huwei Chen ◽  
Shanhe Jiang
Keyword(s):  
Electric Vehicles ◽  
Heterogeneous Networks ◽  
Demand Uncertainty ◽  
Stackelberg Game ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Optimal Decision ◽  
Charging Station ◽  
Simulation Results ◽  
Grid Operators

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.

System dynamics modelling of fixed and dynamic Kanban controlled production systems: a supply chain perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jagan Mohan Reddy K. ◽  
Neelakanteswara Rao A. ◽  
Krishnanand Lanka ◽  
PRC Gopal
Keyword(s):  
Supply Chain ◽  
System Dynamics ◽  
Cycle Time ◽  
Production System ◽  
Demand Uncertainty ◽  
Production Systems ◽  
Decision Variable ◽  
Content Type ◽  
Pull Production ◽  
Kanban System

Purpose Pull production systems have received much attention in the supply chain management environment. The number of Kanbans is a key decision variable in the pull production system as it affects the finished goods inventory (FGI) and backorders of the system. The purpose of this study is to compare the performance of the fixed and dynamic Kanban systems in terms of operational metrics (FGI and backorders) under the demand uncertainty. Design/methodology/approach In this paper, the system dynamics (SD) approach was used to model the performance of fixed and dynamic Kanban based production systems. SD approach has enabled the feedback mechanism and is an appropriate tool to incorporate the dynamic control during the simulation. Initially, a simple Kanban based production system was developed and then compared the performance of production systems with fixed and dynamic controlled Kanbans at the various demand scenarios. Findings From the present study, it is observed that the dynamic Kanban system has advantages over the fixed Kanban system and also observed that the variation in the backorders with respect to the demand uncertainty under the dynamic Kanban system is negligible. Research limitations/implications In a just-in-time production system, the number of Kanbans is a key decision variable. The number of Kanbans is mainly depended on the demand, cycle time, safety stock factor (SSF) and container size. However, this study considered only demand uncertainty to compare the fixed and dynamic Kanban systems. This paper further recommends researchers to consider other control variables which may influence the number of Kanbans such as cycle time, SSF and container size. Originality/value This study will be useful to decision-makers and production managers in the selection of the Kanban systems in uncertain demand applications.

scholarly journals A Flexible Service Rule for the Dynamic Make-to-Stock/Make-to-order Hybrid Production System

2015 ◽  
Vol 2 ◽  
pp. 46-50
Author(s):  
Shohei Kanda ◽  
Katsuhiko Takahashi ◽  
Katsumi Morikawa
Keyword(s):  
Production System ◽  
Hybrid Production ◽  
Make To Order ◽  
Make To Stock

Model Predictive Control of a Forecasting Production System with Deteriorating Items

2015 ◽  
Vol 6 (4) ◽  
pp. 19-37 ◽  
Author(s):  
Abdelhak Mezghiche ◽  
Mustapha Moulaï ◽  
Lotfi Tadj
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Production System ◽  
Objective Function Value ◽  
Inventory Level ◽  
Optimal Production ◽  
Control Approach ◽  
System Parameters ◽  
Demand Rate ◽  
Optimal Inventory Level

The authors consider in this paper an integrated forecasting production system of the tracking type. The demand rate during a certain period depends on the demand rate of the previous period. Also, the demand rate depends on the inventory level. Items on the shelves are subject to deterioration. Using a model predictive control approach, the authors obtain the optimal production rate, the optimal inventory level, the optimal demand rate, and the optimal objective function value, explicitly in terms of the system parameters. A numerical example is presented.

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