Joyce Mei Wan Low

A network prototype for integrated production-distribution planning with non-multi-functional plants

This paper proposes a two-echelon network prototype for integrated production and distribution planning where non-multi-functional plants supply multiple types of products with limited quantities to the customers via capacitated warehouses. Four variations of the prototype, formulated as individual mixed integer programming models, are solved using the branch and bound algorithms by numerical experiments to examine the cost implications of production-distribution strategies involving single-sourcing constraints on different levels of the supply chain. Further discussions on the practicality and versatility of the proposed prototype (i.e. its ability to consider different facility locations, specialised capabilities of individual plants, safety stock levels and demand characteristics) illustrate the usefulness of the prototype to industry practitioners when making strategic and/or tactical decisions.

Network effects in the East Asia container ports industry

This paper proposes an integrated set of 4Cs indices, namely, centrality index, competition index, congestion index and concentration index to examine network effects in the East Asia container port industry. Empirical analysis confirms that larger ports enjoy greater direct network effects related to economies of scale, whereas, smaller ports leverage on indirect network effects to widen their scopes of influence to attract vessel calls. Ports tend to engage in more competitive interactions with their counterparts within the same region, even though cooperative relationships among ports across regions are beneficial. In the light of the empirical results, the paper proceeds to explain some important managerial and policy implications.

Predicting the performance of queues-A data analytic approach

Existing models of multi-server queues with system transience and non-standard assumptions are either too complex or restricted in their assumptions to be used broadly in practice. This paper proposes using data analytics, combining computer simulation to generate the data and an advanced non-linear regression technique called the Alternating Conditional Expectation (ACE) to construct a set of easy-to-use equations to predict the performance of queues with a scheduled start and end time. Our results show that the equations can accurately predict the queue performance as a function of the number of servers, mean arrival load, session length and service time variability. To further facilitate its use in practice, the equations are developed into an open-source online tool accessible at http://singlequeuesystemstool.com/. The proposed procedure of data analytics can be used to model other more complex systems. We propose data analytics as a method for analyzing complex systems.Proposed method combines simulation to generate the data and a non-linear regression technique to analyze the data.Method can be used on multi-server queuing systems with system transience and non-standard service time.The estimation equations developed are very accurate and easy to use.Proposed method can be used for modeling other complex systems.

Modeling queues with simulation versus M/M/C models

This paper examines the performance of single-queue service systems using a combination of computer simulation and M/M/C queuing models. Our results show that the accuracy of M/M/C models is significantly affected by the assumptions supporting the models. Managers should therefore exercise caution in using the M/M/C models for designing queuing systems when the models’ assumptions are violated. Our results show that cost-centric and servicecentric firms should manage their queues differently. While cost-centric firms should target higher arrival load, single service session, and front-loaded arrival pattern for higher efficiency, service-centric firms should strive for lower arrival load, multiple short sessions and even arrival pattern for better service. In addition, both cost-centric and service-centric firms can consider pooling servers together and reducing the variability of inter-arrival and service times to improve both cost and service simultaneously.

An exploratory study on the effects of human, technical and operating factors on aviation safety

ABSTRACT This article explores the effects of human, technical, and operating factors on the safety record of 50 airlines over the period 2004 to 2015. The factors examined include (1) pilot salary, (2) fleet age, (3) International Air Transport Association - Operational Safety Audit (IOSA) certification, (4) International Civil Aviation Organization safety parameters (i.e., legislation, organization, licensing, operations, airworthiness, accident investigation, air navigation service, and aerodromes), and (5) cultural-related indices (such as power distance, degree of uncertainty avoidance, and language for communication). Among the important factors such as organization, licensing, and operations performance, pilot salary is identified as the most important factor differentiating airlines with or without crashes. Within the group of airlines that encountered air accidents during the study period, fleet age, airworthiness, accident investigation, air navigation services and aerodromes scores, and salary are found to be significant factors on accident rate. IOSA certification, aerodromes, language of communi-cation, and uncertainty avoidance appear to be totally immaterial. Identifying the important factors is important to assist airlines investigate and improve their safety records.

On M^{X}/G(M/H)/1 retrial system with vacation: service helpline performance measurement

This paper analyzes an unreliable

Effects of internal resources on airline competitiveness

M^{X}/G(M/H)/1

Managing emergency department crowding through improved triaging and resource allocation

MX/G(M/H)/1 retrial system with vacation. We present closed-form expressions for the important performance indicators of the system, and derive the optimal vacation policies for minimizing the average waiting time of orbiting customers. The performance metrics relevant for helpline services are developed. Numerical experiments are conducted to examine the effect of vacation policy on the queue length and busy period of the system.