A Simulation Model for Decision Support in Business Continuity Planning

Enterprises with a global supply network are at risk of lost revenue as a result of disruptive disasters at supplier locations. Various strategies exist for addressing this risk, and a variety of types of research has been done regarding the identification, assessment and response to the risk of disruption in a supply chain network. This thesis establishes a decision model to support Business Continuity Planning at the first-tier supplier level. The decision model incorporates discrete-event simulation of supply chain networks (through Simio software), Monte Carlo simulation, and risk index optimization. After modeling disruption vulnerability in a supply chain network, costs of implementing all combinations of Business Continuity Plans are ranked and then tested in discrete-event simulation for further insight into inventory levels, unmet customer demand, production loss and related costs. A case study demonstrates the implementation of the decision support process and tests a historical set of data from a large manufacturing company. Discrete-event simulation modeling of loss is confirmed to be accurate. The relevance of the model concept is upheld and recommendations for future work are made

Risk measurement in the global supply chain using monte-carlo simulation

Abstract Nowadays, logistics and supply chain management (SCM) is critical to compete in the current turbulent markets. In addition, in the global context, there are many uncertainties which affect on the market. One of the most important risks is supplier disruption. The first step to cope with these uncertainties is quantifying them. In this regard many researches have focused on the problem but measurement of the risk in the global SCM is yet a challenge. In the uncertain conditions, simulation is a good tool to study the system. This paper aims to study a global supply chain with related risks and measurement of the risks using simulation. Global aspects considered in the paper are: 1-currency exchange rate, 2-extended leadtime for abroad supplies, 3-regional and local uncertainties. In this regard, two popular risk measurement approaches (VaR and CVaR) are used in the simulation of uncertainties in the global supply chain. Results showed that adopting risk averse behavior to cope with the uncertainties leads to the lower stockouts and also higher costs

A Simulation-Based Approach to Risk Assessment and Mitigation in Supply Chain Networks

We present in this paper a simulation-based approach to evaluate the risk associated with supply chain disruptions caused by failures in some supply chains nodes and measure the impact of such disruptions on supply chain key performance measures (KPIs) of interest. The proposed framework enables analysts and managers to repeatedly assess the risk to their supply chains based on various simulated scenarios and identify the most critical nodes whose disruption will have the highest impact on the KPIs of interest. As a result, companies can focus on the most critical supply chain assets and develop targeted mitigation plans that minimize their risk. 2015 The Authors

From Hybrid Simulation to Hybrid Systems Modelling

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Hybrid Simulation (HS) is the combined application of simulation approaches like SD, DES and ABS in the model implementation stage of a simulation study. Its objective is to better represent the system under scrutiny. Hybrid Systems Modelling (HSM), on the other hand, is the combined application of simulation with methods and techniques from disciplines such as Applied Computing, Computer Science, Engineering and the wider OR. HSM can be applied to multiple stages of a simulation study. In this paper, we present a classification of HS and extend it to include HSM approaches which use simulation with other OR techniques. The paper contributes to the debate on what constitutes HS and offers a unifying conceptual representation for mixing simulation approaches with HSM methods and techniques

A Study of the Impact of Information Blackouts on the Bullwhip Effect of a Supply Chain Using Discrete-Event Simulations

This study adds to the supply chain management literature by introducing and investigating information blackouts, sudden and short-duration failure of the information flow. This study aims to contribute to the literature in following ways: first, to define information blackouts in a supply chain. Second, to investigate the response of supply chains to information blackouts using discrete-event simulation. Prior research has focused more on analyzing systemic disruptions to supply chains from well-known sources. We expect the results of this study to be useful to supply chain managers in disaster prone areas

Investigation of the Effect of e-Platform Information Security Breaches: A Small and Medium Enterprise Supply Chain Perspective

Many small and medium enterprises (SMEs) engage in dyadic information integration partnerships or partial integration with their direct suppliers and customers. They often utilise e-commerce or cloud computing technology platforms hosted by third-party providers to leverage such partnerships. However, information security breaches and disruptions caused by cyber-attacks are commonplace in the IT industry. The effects of said disruptions and breaches on e-commerce businesses under varied disruption conditions are still uncertain. Furthermore, the effect of security breaches on non-participating members of the supply chain is poorly understood, especially under various disruption profiles. Using discrete event modelling, this study explores the impact of disruption caused by information security breaches on supply chain performance and the externality effect of partial integration on non-participants. We also examine the impact of breach disruption frequency and remediation length on supply chain performance with varying levels of information sharing. These impacts were studied under two typical inventory replenishment policies for SMEs. It was determined that remediation length should be a prioritised factor in impact management and that flexibility in the inventory replenishment policy can help mitigate the impact of information disruption on the inventory performance of businesses, especially that of non-participants, in information-sharing partnerships

A contribution to supply chain design under uncertainty

Dans le contexte actuel des chaînes logistiques, des processus d'affaires complexes et des partenaires étendus, plusieurs facteurs peuvent augmenter les chances de perturbations dans les chaînes logistiques, telles que les pertes de clients en raison de l'intensification de la concurrence, la pénurie de l'offre en raison de l'incertitude des approvisionnements, la gestion d'un grand nombre de partenaires, les défaillances et les pannes imprévisibles, etc. Prévoir et répondre aux changements qui touchent les chaînes logistiques exigent parfois de composer avec des incertitudes et des informations incomplètes. Chaque entité de la chaîne doit être choisie de façon efficace afin de réduire autant que possible les facteurs de perturbations. Configurer des chaînes logistiques efficientes peut garantir la continuité des activités de la chaîne en dépit de la présence d'événements perturbateurs. L'objectif principal de cette thèse est la conception de chaînes logistiques qui résistent aux perturbations par le biais de modèles de sélection d'acteurs fiables. Les modèles proposés permettent de réduire la vulnérabilité aux perturbations qui peuvent aV, oir un impact sur la continuité des opérations des entités de la chaîne, soient les fournisseurs, les sites de production et les sites de distribution. Le manuscrit de cette thèse s'articule autour de trois principaux chapitres: 1 - Construction d'un modèle multi-objectifs de sélection d'acteurs fiables pour la conception de chaînes logistiques en mesure de résister aux perturbations. 2 - Examen des différents concepts et des types de risques liés aux chaînes logistiques ainsi qu'une présentation d'une approche pour quantifier le risque. 3 - Développement d'un modèle d'optimisation de la fiabilité afin de réduire la vulnérabilité aux perturbations des chaînes logistiques sous l'incertitude de la sollicitation et de l'offre

Towards a model for managing uncertainty in logistics operations – A simulation modeling perspective

Uncertainty rules supply chains. Unexpected changes constantly occur on all levels; strategically through globalization, introduction of novel technology, mergers and acquisitions, volatile markets, and on an operational level through demand fluctuations, and events such as late arrival of in-bound material, machine equipment breakdown, and quality problems. The problem with uncertainty is increasing as the focus on cost reductions and efficiency in the industry tends to stretch supply chains to become longer and leaner, thus making them more vulnerable to disturbances. The aim of this thesis is to explore strategies for evaluating and managing uncertainties in a logistics context with the objectives; “to propose a method for modeling and analyzing the dynamics of logistics systems with an emphasize on risk management aspects”, and “to explore the impact of dynamic planning and execution in a logistics system”. Three main strategies for handling uncertainties are being discussed; robustness, reliability, and resilience. All three strategies carry an additional cost that must be weighed against the cost and risk of logistical disruptions. As an aid in making this trade-off, a hybrid simulation approach, based on discrete-event simulation and Monte Carlo simulation, is proposed. A combined analytical, and simulation approach is further used to explore the impact of dynamic planning and execution in a solid waste management case. Finally, a draft framework for how uncertainty can be managed in a logistics context is presented along with the key reasons why the proposed simulation approach has proven itself useful in the context of logistics systems

Applications of simulation within the healthcare context

This is a pre-print of an article published in Journal of the Operation Research Society. The definitive publisher-authenticated version Katsaliaki, K., Mustafee, N.,(2010). Applications of simulation within the healthcare context. Journal of the Operation Research Society. 62, 1431-1451 is available online at: http://www.palgrave-journals.com/jors/journal/v62/n8/full/jors201020a.htmlA large number of studies have applied simulation to a multitude of issues related to healthcare. These studies have been published over a number of unrelated publishing outlets, and this may hamper the widespread reference and use of such resources. In this paper we analyse existing research in healthcare simulation in order to categorise and synthesise it in a meaningful manner. Hence, the aim of this paper is to conduct a review of the literature pertaining to simulation research within healthcare in order to ascertain its current development. A review of approximately 250 high quality journal papers published between 1970 and 2007 on healthcare-related simulation research was conducted. The results present: a classification of the healthcare publications according to the simulation techniques they employ; the impact of published literature in healthcare simulation; a report on demonstration and implementation of the studies’ results; the sources of funding; and the software used. Healthcare planners and researchers will benefit from this study by having ready access to an indicative article collection of simulation techniques applied in healthcare problems that are clustered under meaningful headings. This study facilitates the understanding of the potential of different simulation techniques for solving diverse healthcare problems