scholarly journals Multi-Period Age-Discriminated Perishable Inventory

2021 ◽  
Vol 29 (2) ◽  
pp. 97-105
Author(s):  
Wasfi Alrawabdeh
Keyword(s):  
Simulated Annealing Algorithm ◽  
Discrete Event ◽  
Stochastic Demand ◽  
Pharmaceutical Products ◽  
Optimal Order ◽  
Order Quantity ◽  
Event Simulation ◽  
Simulation Based ◽  
Optimal Order Quantity ◽  
Packaged Food

Abstract In this paper, an extremely short shelf-life inventory of age-discriminated stochastic demand is considered. Age discriminated demand can be found in products of high circulation and short shelf-lives such as dairy products, packaged food, pharmaceutical products and medical products of short shelf lives. Simulation based optimization is considered to find the optimal order quantity. The model employs Discrete Event Simulation along with a modified simulated annealing algorithm. To validate the model and the optimization algorithm, the classical newsvendor problem is tested first, later, different experiments are carried out for different product lifetimes. In contrast to the classical newsvendor, this problem tackles a multi-period inventory of different ages and different demand distributions. The objective is to determine the optimal order quantity to satisfy the stochastic demand of all ages such that shortages and expirations are minimized. The results showed remarkable performance and outstanding minimum levels of shortage and expiration.

scholarly journals Enhanced coverage by integrating site interdependencies in capacitated EMS location models

2021 ◽  
Author(s):  
Matthias Grot ◽  
Tristan Becker ◽  
Pia Mareike Steenweg ◽  
Brigitte Werners
Keyword(s):  
Discrete Event ◽  
Mathematical Formulation ◽  
Optimization Approach ◽  
Solution Quality ◽  
Similar System ◽  
Event Simulation ◽  
Simulation Based ◽  
Average System ◽  
Simplifying Assumptions ◽  
A Site

AbstractIn order to allocate limited resources in emergency medical services (EMS) networks, mathematical models are used to select sites and their capacities. Many existing standard models are based on simplifying assumptions, including site independency and a similar system-wide busyness of ambulances. In practice, when a site is busy, a call is forwarded to another site. Thus, the busyness of each site depends not only on the rate of calls in the surrounding area, but also on interactions with other facilities. If the demand varies across the urban area, assuming an average system-wide server busy fraction may lead to an overestimation of the actual coverage. We show that site interdependencies can be integrated into the well-known Maximum Expected Covering Location Problem (MEXCLP) by introducing an upper bound for the busyness of each site. We apply our new mathematical formulation to the case of a local EMS provider. To evaluate the solution quality, we use a discrete event simulation based on anonymized real-world call data. Results of our simulation-optimization approach indicate that the coverage can be improved in most cases by taking site interdependencies into account, leading to an improved ambulance allocation and a faster emergency care.

scholarly journals Coping with Loss Aversion in the Newsvendor Model

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jianwu Sun ◽  
Xinsheng Xu
Keyword(s):  
Expected Utility ◽  
Loss Aversion ◽  
Confidence Level ◽  
Profit Maximization ◽  
Optimal Order ◽  
Market Demand ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Decision Bias ◽  
Optimal Order Quantity

We introduce loss aversion into the decision framework of the newsvendor model. By introducing the loss aversion coefficientλ, we propose a novel utility function for the loss-averse newsvendor. First, we obtain the optimal order quantity to maximize the expected utility for the loss-averse newsvendor who is risk-neutral. It is found that this optimal order quantity is smaller than the expected profit maximization order quantity in the classical newsvendor model, which may help to explain the decision bias in the classical newsvendor model. Then, to reduce the risk which originates from the fluctuation in the market demand, we achieve the optimal order quantity to maximize CVaR about utility for the loss-averse newsvendor who is risk-averse. We find that this optimal order quantity is smaller than the optimal order quantity to maximize the expected utility above and is decreasing in the confidence levelα. Further, it is proved that the expected utility under this optimal order quantity is decreasing in the confidence levelα, which verifies that low risk implies low return. Finally, a numerical example is given to illustrate the obtained results and some management insights are suggested for the loss-averse newsvendor model.

Virtual production planning of a high-speed train using a discrete event simulation based approach

2013 ◽  
Vol 9 (1) ◽  
pp. 65-75 ◽  
Author(s):  
Giuseppe Di Gironimo ◽  
Antonio Lanzotti ◽  
Fabio Peluso ◽  
Fabrizio Renno
Keyword(s):  
Production Planning ◽  
Discrete Event Simulation ◽  
High Speed ◽  
Discrete Event ◽  
High Speed Train ◽  
Event Simulation ◽  
Virtual Production ◽  
Simulation Based

scholarly journals Coordination of Supply Chain with One Supplier and Two Competing Risk-Averse Retailers under an Option Contract

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Rui Wang ◽  
Shiji Song ◽  
Cheng Wu
Keyword(s):  
Supply Chain ◽  
Conditional Value At Risk ◽  
Optimal Order ◽  
Pareto Optimum ◽  
Risk Averse ◽  
Order Quantity ◽  
Supply Chain System ◽  
Chain System ◽  
Option Contract ◽  
Optimal Order Quantity

This paper studies an option contract for coordinating a supply chain comprising one risk-neutral supplier and two risk-averse retailers engaged in promotion competition in the selling season. For a given option contract, in decentralized case, each risk-averse retailer decides the optimal order quantity and the promotion policy by maximizing the conditional value-at-risk of profit. Based on the retailers’ decision, the supplier derives the optimal production policy by maximizing expected profit. In centralized case, the optimal decision of the supply chain system is obtained. Based on the decentralized and centralized decision, we find the coordination conditions of the supply chain system, which can optimize the supply chain system profit and make the profits of the supply chain members achieve Pareto optimum. As for the subchain, we also find the coordination conditions, which generalize the results of the supply chain with one supplier and one retailer. Our analysis and numerical experiments show that there exists a unique Nash equilibrium between two retailers, and the optimal order quantity of each retailer increases (decreases) with its own (competitor’s) promotion level.

scholarly journals Trade Credit with Barter in a Capital-Constrained Supply Chain

2021 ◽  
Vol 13 (20) ◽  
pp. 11361
Author(s):  
Yangyang Huang ◽  
Zhenyang Pi ◽  
Weiguo Fang
Keyword(s):  
Supply Chain ◽  
Trade Credit ◽  
Wholesale Price ◽  
Uncertain Demand ◽  
Equilibrium Strategy ◽  
Optimal Order ◽  
Order Quantity ◽  
Supply Rate ◽  
Optimal Order Quantity ◽  
And Performance

Barter has emerged to alleviate capital pressure, maximize the circulation of goods, and facilitate the disposal of excess inventory. This study considers a two-level supply chain consisting of a manufacturer and a capital-constrained retailer with trade credit, in which the retailer exchanges unsold products for needed subsidiary products on a barter platform. The retailer’s optimal order quantity and the manufacturer’s wholesale price are derived, and the influences of barter and other factors on the equilibrium strategy and performance of the supply chain are examined; these results are verified and supplemented by numerical simulation. We find that the retailer can increase profit by bartering when facing highly uncertain demand, that the retailer’s optimal order quantity increases with the supply rate and demand for subsidiary products, and that both manufacturer and retailer benefit from the high supply rate of subsidiary products. However, barter induces the manufacturer to raise the wholesale price to prevent its profit from being harmed. In addition, the manufacturer suffers from the retailer’s initial capital.

Abstract 2524: Increasing the Proportion of Patients Treated with Stroke Thrombolysis: Reducing In-hospital Delays has Substantially More Impact than Extension of the Time Window

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Martin A James ◽  
Thomas Monks ◽  
Ken Stein ◽  
Martin Pitt
Keyword(s):  
Time Window ◽  
Discrete Event ◽  
Fold Increase ◽  
Service Improvement ◽  
Disability Benefit ◽  
Prospective Data ◽  
Stroke Service ◽  
Event Simulation ◽  
Simulation Based ◽  
The Impact

Background Pooled analyses show the benefit of IV alteplase for ischemic stroke up to 4·5 hours after onset, and expert guidelines have been updated to reflect this. However, the benefit from thrombolysis is critically time-dependent, and the additional benefit from extending the time window may be jeopardised by in-hospital delays. Methods We developed a discrete-event simulation based on prospective data from 1142 acute stroke patients arriving at our large district hospital over a two-year period to April 2011, modelling the time spent in the ED for triage and assessment, brain imaging and, if applicable, thrombolysis. Outputs from the model included arrival to treatment times (ATT), percentage of strokes thrombolysed, and the number of thrombolysed patients with a 90 day modified Rankin Scale (mRS) of 0-1. We sought to model the current stroke pathway (treatment <3 hours of onset), and compare it with developmental scenarios exploring the impact of extending treatment from 3 to 4.5 hours, of ED staff alerting the stroke service at triage, of ambulance pre-alert to the stroke service, and combinations of these measures. Results The model illustrates that extending the treatment window modestly increases the percentage of acute strokes thrombolysed, from 5% to 6% (95% CI 5.8-6.1%), and increases the number of thrombolysed patients with mRS 0-1 by 7 per year (95% CI 5.9-8.0). Both the triage alert and ambulance pre-alert scenarios increase thrombolysis rates to 15% (95% CI 14.9% to 15.7%); but the ambulance pre-alert reduces ATT by a mean of 27 mins (95% CI 26.3-28.4) compared to the triage alert scenario. The ambulance pre-alert scenario increases the number of thrombolysed patients with mRS 0-1 by 35/year (95% CI 32.9-37.7) compared to 22 (95% CI 20.4-23.5) in the triage alert scenario. Combining the treatment extension with either alerting measure does not increase the thrombolysis rate further (15%, 95% CI 14.7-15.1%). Sensitivity analysis illustrates that the pre-alert system is the least vulnerable to a drop in compliance rates. Conclusions Our simulation model shows that the greatest disability benefit accrues from measures to substantially reduce in-hospital delays to alteplase treatment - a potential three-fold increase in the proportion of patients treated. Compared to extending the time window for alteplase from 3 to 4.5 hours, eradicating in-hospital delays to treatment offers a five-fold greater disability benefit, and this should be the pre-eminent focus of service improvement for all emergency receiving hospitals.

Discrete-Event-Simulation Based on Machine Learning Predictive Agents

2021 ◽  
pp. 609-619
Author(s):  
Javier Andión ◽  
Juan C. Dueñas ◽  
Félix Cuadrado
Keyword(s):  
Machine Learning ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Event Simulation ◽  
Simulation Based
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