Simulation Modeling Approach for Evaluating a Solution Designed to Alleviate the Congestion of Passenger Flow at the Composure Area of Security Checkpoints

In a previous study, we found that replacing the exit roller of a security checkpoint lane for a continuously circulating conveyor could potentially increase the throughput of passengers by over 28% while maintaining the TSA security-waiting time limit (Janer and Rossetti 2016). This study intends to expand this previous effort by investigating the impact of this circulating conveyor on the secondary screening related processes. Leone and Liu (2011) found that imposing a limit on the x-ray screening time, and diverting any item exceeding this limit to secondary screening, could decrease the waiting time by 43%. Our objective is to verify Leone and Lui’s findings using discrete event simulation, and evaluate the effect of a circulating conveyor on these findings. In particular, we intend to optimize univariate response curves of the same response variable in Leone and Liu’s effort. Simulation will be used to evaluate the optimal solution, and investigate the possibility of replacing a traditional two-lane system with a single lane having the circulating conveyor in place

A Classification and Assessment of Research Streams on Low Cost Modeling in Civil Aviation Transportation Industry

This article attempts to identify key research streams in Civil Aviation Transportation Industry during the past decade and highlights the evolution of the literature. Progress in six established research thrusts and a new research stream is discussed. Using content analysis, the existing research is also examined from a methodological point of view. The review provides evidence for an increasingly sophisticated and rich body of knowledge in global Civil Aviation Transportation Industry. Keywords: Civil Aviation Transportation Industry (CATI), Low Cost Strategies (LCS), Low Cost Carriers (LCCs), Classification, Assessment

Simulation Of Passenger Flow For International Departure Using Witness Horizon

The focus of the paper is to investigate the passenger flow in airport terminal in Kulim International Airport (KXP). There are some processes involved in the international departure in airport terminal such as check-in profile, security screening of passengers and baggage, and departure passport check. The objective of the paper is to investigate the number of machines and labours required through WITNESS simulation during peak hours in weekdays, weekends and holiday season. This research was proposed based on Kulim International Airport (KXP) project that is currently in planning stage. There are three different models that simulate the passenger flow in the check-in area, security screening and passport check in three different scenarios. The unhappiness of passenger is the parameter to measure whether the model is suitable to implement in real life. Unhappiness of passengers is based on the waiting time required in each section. Long waiting time may cause congestion and flight delays. The simulation result is based on unhappiness of passengers and an improved solution is needed when the unhappiness is more than 10%. The result of each model is analysed based on machines, buffers and labors performance. Each section is then compared based on percentage of busy, percentage of idle, number of operations, average waiting time and others. An optimum model is created when the unhappiness of passengers exceeds 10%. The proposed simulation layout is compared with the current layout with a better performance in reduce passengers’ waiting time in airport terminal

Prevention of terrorism : an assessment of prior POM work and future potentials

© 2020 Production and Operations Management Society In this study, we review POM-based research related to prevention of terrorism. According to the Federal Emergency Management Agency (FEMA) terrorist attacks have the potential to be prevented. Consequently, the focus of this study is on security enhancement and improving the resiliency of a nation to prevent terrorist attacks. Accordingly, we review articles from the 25 top journals, [following procedures developed by Gupta et al. (2016)], in the fields of Production and Operations Management, Operations Research, Management Science, and Supply Chain Management. In addition, we searched some selected journals in the fields of Information Sciences, Political Science, and Economics. This literature is organized and reviewed under the following seven core capabilities defined by the Department of Homeland Security (DHS): (1) Intelligence and Information Sharing, (2) Planning, (3) Interdiction and Disruption, (4) Screening, Search, and Detection, (5) Forensics and Attribution, (6) Public Information and Warning, and (7) Operational Coordination. We found that POM research on terrorism is primarily driven by the type of information that a defending country and a terrorist have about each other. Game theory is the main technique that is used in most research papers. Possible directions for future research are discussed

Disruptions in International Trade: A Perspective on Ports of Entry and Supply Chain Resilience

United States (U.S.) ports of entry (POEs) and supply chains (SCs) have a prominent trade relationship with a growing desire to improve their operational capabilities. Though trade deals like the U.S.-Mexico-Canada (USMCA) agreement have facilitated trade between these countries, U.S. Customs and Border Protection (CBP) at POEs have also increased security inspections, following the September 11th incident, which have impacted international and global SCs. More recently, the COVID-19 pandemic has caused labor shortages at both sea and land POEs, increasing vessel and commercial vehicle congestion. These POE disruptions have also propagated into the third-party logistics (3PL) of SC networks, which has increased transportation costs. In this thesis, we explored operational improvement strategies from the perspectives of the public sector (i.e., U.S.-Mexico POEs) and the private sector (i.e., 3PL SC networks). The goal of this study was to understand the relationship between transportation disruptions and international trade

Planning Border Controls at UK Airports: Quantitative studies into operational decisions and their impact on passengers

This thesis contains three new research projects in the field of airport border control. Utilising unique access to the UK Home Office and Border Force, these studies combine current and historic data of airport border control scenarios with advanced quantitative methods to provide novel analysis of passenger delays and their costs. This analysis is framed in terms of the significant rise in global air passenger numbers in recent decades and the major technological, operational and information changes that have occurred in response. The overall aim has been to consider areas where these new forms of airport border controls may continue to be operating in ways that result in suboptimal outcomes for passengers; in terms of both average wait times and the frequency of ‘unacceptably’ long delays. Whilst there is a vast literature exploring this field in terms of the theoretical impact of new systems of border control, there are few that explore the objectives of operational decisions or provide empirical evidence to evaluate their underlying logic. I attempt to rectify this by exploring three specific elements of the border system, using UK airports as a case study. The first project considers the impact that the stochasticity of flight arrival times has on the risks that long wait times will occur at non-automated border controls. Whilst authorities receive prior information on the number of flights, passengers, and passenger type, it cannot predict exactly what time those flights will arrive. Using stochastic Discrete Event Simulation (DES) of a UK airport terminal, we identify the wide range of border delays that occur from this single variable and suggest the staffing decisions that would be necessary to ameliorate this risk. My second project explores the costs of variances in border processing times by nationality. Using the results of observational research at various UK ports, I establish the average times that different nationalities spend at staffed desks. These are then included in an updated version of our DES model to show the link between processing rates and border delays. Further analysis illustrates the savings that could be achieved from ‘levelling down’ processing times for nationalities facing the highest challenge to their border. The final project switches to analysing newer automated border controls (eGates). Using results from a stated preference survey, I challenge existing valuations of travel time suggested for passengers in these systems and provide new insight into how the full arrival process needs to be considered when costing delays. DES modelling of multiple UK airports is then used to provide examples of how both time and operational costs vary as the level of eGate provision changes. I conclude from these results that the passenger time costs of an undersupply of gates will often significantly exceed the redundant operational costs of an oversupply

Framework development for improving arrival processing of pilgrims at Hajj and Umrah airport terminals

Millions of Muslims around the world perform the Hajj, a mandatory religious journey to the holy city of Mecca, at least once in their lifetime. Therefore, hundreds of thousands of pilgrims arrive weekly at Jeddah and Medina Airports during the Hajj period determined by the Islamic calendar. Numerous research studies have been published on the health, security, risk management and logistics aspects of the mass gathering. However, studies on pilgrims’ wait times, flow and satisfaction at the Hajj and Umrah Terminals (HT)s are very limited. The research evaluating the inbound passenger domain is especially limited. Therefore, this study contributes to the literature by combining different perspectives regarding the inefficiency of HT processes. Furthermore, this study proposes and investigates various aspects to improve the processing of arriving passengers at HTs. It does so by identifying and studying the factors that impede the flow of passengers within these terminals from users’ and providers’ perspectives. This research aims to contribute by developing an innovative integrated framework to improve the flow of pilgrims through arrival terminals and determining how large crowds at airports can be better managed. To meet the study’s aims, a simulation model is developed to verify and confirm the performance of arrival passenger processes at HTs by conducting a mixedmethods analysis and integrating the numerical results of the agent-based and discrete-event simulation models. This study creates a problematic review matrix based on users’ and providers’ perspectives. In addition, the survey on providers’ perspectives indicates that there are five factors, human, infrastructure, operational, technical and organisational factors, influencing arrival passenger processes at HTs and interacting with level of service (LoS) variables. The study indicates the suboptimal processes at airport terminals to focus on the factors negatively affecting the HT processes. In addition, the research highlights the role of terminal configurations. This study compares two airports in terms of peak demand patterns. According to the study, sharp peaks can have strong negative impacts on HTs, while evenly distributed demand can improve LoS at HTs. The simulation model outcomes verify and confirm the parameters and factors influencing LoS. In addition, the study’s integrated framework provides diverse viewpoints on the operational processes at HTs, while the density map matrix helps to classify the processes. This study applies what-if scenarios to identify the impact of pilgrims’ experience and biometric characteristics and finds that inexperience and certain biometric characteristics have negative impacts on LoS. Limitations of the study and suggestions for future research are discussed.Transport System

Multi-scale Models for Transportation Systems Under Emergency Conditions

The purpose of this study is to investigate human behavior in emergencies. More specifically, agent-based simulation and social force models were developed to examine the impact of various human and environmental factors on the efficiency of the evacuation process, through a series of case studies. The independent variables of the case studies include the number of exits, the number of passengers, the evacuation policies, and instructions, as well as the queue configuration and wall separators. The results revealed the location of the exits, number of exits, evacuation strategies, and group behaviors all significantly impact the total time of the evacuation. For the queue configuration, short aisles lower infection spread when rope separators were used. The findings provide new insights in designing layout, planning, practice, and training strategies for improving the effectiveness of the pedestrian evacuation process under emergency

Computing resources sensitive parallelization of neural neworks for large scale diabetes data modelling, diagnosis and prediction

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Diabetes has become one of the most severe deceases due to an increasing number of diabetes patients globally. A large amount of digital data on diabetes has been collected through various channels. How to utilize these data sets to help doctors to make a decision on diagnosis, treatment and prediction of diabetic patients poses many challenges to the research community. The thesis investigates mathematical models with a focus on neural networks for large scale diabetes data modelling and analysis by utilizing modern computing technologies such as grid computing and cloud computing. These computing technologies provide users with an inexpensive way to have access to extensive computing resources over the Internet for solving data and computationally intensive problems. This thesis evaluates the performance of seven representative machine learning techniques in classification of diabetes data and the results show that neural network produces the best accuracy in classification but incurs high overhead in data training. As a result, the thesis develops MRNN, a parallel neural network model based on the MapReduce programming model which has become an enabling technology in support of data intensive applications in the clouds. By partitioning the diabetic data set into a number of equally sized data blocks, the workload in training is distributed among a number of computing nodes for speedup in data training. MRNN is first evaluated in small scale experimental environments using 12 mappers and subsequently is evaluated in large scale simulated environments using up to 1000 mappers. Both the experimental and simulations results have shown the effectiveness of MRNN in classification, and its high scalability in data training. MapReduce does not have a sophisticated job scheduling scheme for heterogonous computing environments in which the computing nodes may have varied computing capabilities. For this purpose, this thesis develops a load balancing scheme based on genetic algorithms with an aim to balance the training workload among heterogeneous computing nodes. The nodes with more computing capacities will receive more MapReduce jobs for execution. Divisible load theory is employed to guide the evolutionary process of the genetic algorithm with an aim to achieve fast convergence. The proposed load balancing scheme is evaluated in large scale simulated MapReduce environments with varied levels of heterogeneity using different sizes of data sets. All the results show that the genetic algorithm based load balancing scheme significantly reduce the makespan in job execution in comparison with the time consumed without load balancing.This work is funded by the EPSRC and China Market Association

Proceedings, MSVSCC 2011

Proceedings of the 5th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 14, 2011 at VMASC in Suffolk, Virginia. 186 pp