Discrete Event Simulation in Inventory Management

2019 ◽  
pp. 977-988
Author(s):  
Linh Nguyen Khanh Duong ◽  
Lincoln C. Wood
Keyword(s):  
Inventory Management ◽  
Discrete Event ◽  
Simulation Models ◽  
Uncertain Demand ◽  
Perishable Products ◽  
Chain Management ◽  
Perishable Inventory ◽  
Event Simulation ◽  
Multiple Products ◽  
Alternative Product

Perishability and substitutability are two key attributes that cannot be ignored in supply chain management. Once produced, perishable products have a finite shelf life. When expired, they are either partially or wholly value-less. The more time that perishable inventory is in storage, the less time it is available for sale to customers. Product substitution is a possibility when considering multiple products. Research indicates that an alternative product is willingly chosen by customers if the preferred one is out of stock. Managers must decide on the replenishment time and replenishment quantity for each item within product subcategory to maximize expected profits under uncertain demand while minimizing the instances of running out of inventory (i.e., a stock out). The combination of these factors often requires simulation models to be developed to understand the behavior of the system as the parameters change. Simulation can incorporate stochasticity and complexity while providing detailed output for further analysis and optimization work.

Discrete Event Simulation in Inventory Management

2018 ◽  
pp. 5335-5344
Author(s):  
Linh Nguyen Khanh Duong ◽  
Lincoln C. Wood
Keyword(s):  
Inventory Management ◽  
Discrete Event ◽  
Simulation Models ◽  
Uncertain Demand ◽  
Perishable Products ◽  
Chain Management ◽  
Perishable Inventory ◽  
Event Simulation ◽  
Multiple Products ◽  
Alternative Product

Perishability and substitutability are two key attributes that cannot be ignored in supply chain management. Once produced, perishable products have a finite shelf life. When expired, they are either partially or wholly value-less. The more time that perishable inventory is in storage, the less time it is available for sale to customers. Product substitution is a possibility when considering multiple products. Research indicates that an alternative product is willingly chosen by customers if the preferred one is out of stock. Managers must decide on the replenishment time and replenishment quantity for each item within product subcategory, to maximize expected profits under uncertain demand while minimizing the instances of running out of inventory (i.e., a ‘stock out'). The combination of these factors often requires simulation models to be developed to understand the behavior of the system as the parameters change. Simulation can incorporate stochasticity and complexity while providing detailed output for further analysis and optimization work.

scholarly journals Simulation modeling and analysis of primary health center operations

SIMULATION ◽  
2021 ◽  
pp. 003754972110309
Author(s):  
Mohd Shoaib ◽  
Varun Ramamohan
Keyword(s):  
Resource Utilization ◽  
Waiting Times ◽  
Discrete Event ◽  
Simulation Models ◽  
Modeling And Analysis ◽  
Healthcare Facilities ◽  
Event Simulation ◽  
Analytical Approximations ◽  
Primary Health ◽  
Generic Modeling

We present discrete-event simulation models of the operations of primary health centers (PHCs) in the Indian context. Our PHC simulation models incorporate four types of patients seeking medical care: outpatients, inpatients, childbirth cases, and patients seeking antenatal care. A generic modeling approach was adopted to develop simulation models of PHC operations. This involved developing an archetype PHC simulation, which was then adapted to represent two other PHC configurations, differing in numbers of resources and types of services provided, encountered during PHC visits. A model representing a benchmark configuration conforming to government-mandated operational guidelines, with demand estimated from disease burden data and service times closer to international estimates (higher than observed), was also developed. Simulation outcomes for the three observed configurations indicate negligible patient waiting times and low resource utilization values at observed patient demand estimates. However, simulation outcomes for the benchmark configuration indicated significantly higher resource utilization. Simulation experiments to evaluate the effect of potential changes in operational patterns on reducing the utilization of stressed resources for the benchmark case were performed. Our analysis also motivated the development of simple analytical approximations of the average utilization of a server in a queueing system with characteristics similar to the PHC doctor/patient system. Our study represents the first step in an ongoing effort to establish the computational infrastructure required to analyze public health operations in India and can provide researchers in other settings with hierarchical health systems, a template for the development of simulation models of their primary healthcare facilities.

scholarly journals Assessing asset monitoring levels for maintenance operations

2015 ◽  
Vol 26 (5) ◽  
pp. 632-659 ◽  
Author(s):  
Abdullah A Alabdulkarim ◽  
Peter Ball ◽  
Ashutosh Tiwari
Keyword(s):  
Asset Management ◽  
Business Models ◽  
Discrete Event ◽  
Dynamic Modelling ◽  
Simulation Models ◽  
Content Type ◽  
Event Simulation ◽  
Product Service ◽  
Asset Monitoring ◽  
The Impact

Purpose – Asset management has recently gained significance due to emerging business models such as Product Service Systems where the sale of asset use, rather than the sale of the asset itself, is applied. This leaves the responsibility of the maintenance tasks to fall on the shoulders of the manufacturer/supplier to provide high asset availability. The use of asset monitoring assists in providing high availability but the level of monitoring and maintenance needs to be assessed for cost effectiveness. There is a lack of available tools and understanding of their value in assessing monitoring levels. The paper aims to discuss these issues. Design/methodology/approach – This research aims to develop a dynamic modelling approach using Discrete Event Simulation (DES) to assess such maintenance systems in order to provide a better understanding of the behaviour of complex maintenance operations. Interviews were conducted and literature was analysed to gather modelling requirements. Generic models were created, followed by simulation models, to examine how maintenance operation systems behave regarding different levels of asset monitoring. Findings – This research indicates that DES discerns varying levels of complexity of maintenance operations but that more sophisticated asset monitoring levels will not necessarily result in a higher asset performance. The paper shows that it is possible to assess the impact of monitoring levels as well as make other changes to system operation that may be more or less effective. Practical implications – The proposed tool supports the maintenance operations decision makers to select the appropriate asset monitoring level that suits their operational needs. Originality/value – A novel DES approach was developed to assess asset monitoring levels for maintenance operations. In applying this quantitative approach, it was demonstrated that higher asset monitoring levels do not necessarily result in higher asset availability. The work provides a means of evaluating the constraints in the system that an asset is part of rather than focusing on the asset in isolation.

scholarly journals Evaluation of a proposed optimization method for discrete-event simulation models

2012 ◽  
Vol 32 (3) ◽  
pp. 543-560 ◽  
Author(s):  
Alexandre Ferreira de Pinho ◽  
José Arnaldo Barra Montevechi ◽  
Fernando Augusto Silva Marins ◽  
Rafael Florêncio da Silva Costa ◽  
Rafael de Carvalho Miranda ◽  
...  
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Simulation Models ◽  
Optimization Method ◽  
Event Simulation

Using Object-Oriented Frame Language for Realizing Discrete Event Simulation

1996 ◽  
Author(s):  
Ming Dong ◽  
Jianzhong Cha ◽  
Mingcheng E
Keyword(s):  
Knowledge Base ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Object Oriented ◽  
Simulation Models ◽  
Activity Cycle ◽  
Event Simulation ◽  
Knowledge Based ◽  
Inference Engines ◽  
Reasoning About Knowledge

Abstract In this paper, we realize knowledge-based discrete event simulation model’s representation, reasoning and implementation by means of object-oriented(OO) frame language. Firstly, a classes library of simulation models is built by using the OO frame language. And then, behaviours of simulation models can be generated by inference engines reasoning about knowledge base. Lastly, activity cycle diagrams can be used to construct simulation network logic models by connecting the components classes of simulation models. This kind of knowledge-based simulation models can effectively solve the modeling problems of complex and ill-structure systems.

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