EUROPEAN CONFERENCE ON QUEUEING THEORY 2016

International audienceThis booklet contains the proceedings of the second European Conference in Queueing Theory (ECQT) that was held from the 18th to the 20th of July 2016 at the engineering school ENSEEIHT, Toulouse, France. ECQT is a biannual event where scientists and technicians in queueing theory and related areas get together to promote research, encourage interaction and exchange ideas. The spirit of the conference is to be a queueing event organized from within Europe, but open to participants from all over the world. The technical program of the 2016 edition consisted of 112 presentations organized in 29 sessions covering all trends in queueing theory, including the development of the theory, methodology advances, computational aspects and applications. Another exciting feature of ECQT2016 was the institution of the Takács Award for outstanding PhD thesis on "Queueing Theory and its Applications"

BIBS: A Lecture Webcasting System

The Berkeley Internet Broadcasting System (BIBS) is a lecture webcasting system developed and operated by the Berkeley Multimedia Research Center. The system offers live remote viewing and on-demand replay of course lectures using streaming audio and video over the Internet. During the Fall 2000 semester 14 classes were webcast, including several large lower division classes, with a total enrollment of over 4,000 students. Lectures were played over 15,000 times per month during the semester. The primary use of the webcasts is to study for examinations. Students report they watch BIBS lectures because they did not understand material presented in lecture, because they wanted to review what the instructor said about selected topics, because they missed a lecture, and/or because they had difficulty understanding the speaker (e.g., non-native English speakers). Analysis of various survey data suggests that more than 50% of the students enrolled in some large classes view lectures and that as many as 75% of the lectures are played by members of the Berkeley community. Faculty attitudes vary about the virtues of lecture webcasting. Some question the use of this technology while others believe it is a valuable aid to education. Further study is required to accurately assess the pedagogical impact that lecture webcasts have on student learning

Optimal and Heuristic Resource Allocation Policies in Serial Production Systems

We have studied the optimal server allocation policies for a tandem queueing system under different system settings. Motivated by an industry project, we have studied a two stage tandem queueing system with arrival to the system and having two flexible servers capable of working at either of the stations. In our research, we studied the system under two different circumstances: modeling the system to maximize throughput without cost considerations, modeling the system to include switching and holding costs along with revenue for finished goods. In the maximizing throughput scenario, we considered two different types of server allocations: collaborative and non-collaborative. For the collaborative case, we identified the optimal server allocation policies for the servers and have proved the structure of the optimal server allocation policy using mathematical iteration techniques. Moreover, we found that, it is optimal to allocate both the servers together all the time to get maximum throughput. In the non-collaborative case, we have identified the optimal server allocation policies and found that it is not always optimal to allocate both the servers together. With the inclusion of costs, we studied the system under two different scenarios: system with switching costs only and system having both switching and holding costs. In both the cases, we have studied the optimal server allocation policies for the servers. Due to the complicated structure of the optimal server allocation policy, we have studied three different heuristics to approximate the results of the optimal policy. We found that the performance of one of the heuristics is very close to the optimal policy values

Establishing agent staffing levels in queueing systems with cross-trained and specialized agents

The determination of the right number of servers in a multi-server queueing system is one of the most important problems in applied queueing theory. The problem becomes more complex in a system that consists of both cross-trained and specialized servers. Such queueing systems are readily found in the call centres (also called contact centres) of financial institutions, telemarketing companies and other organizations that provide services to customers in multiple languages. They are also found in computer network systems where some servers are dedicated and others are flexible enough to handle various clients' requests. Over-staffing of these systems causes increased labour costs for the underutilized pool of agents on duty, while under-staffing results in reduced revenue from lost customers and an increase in queue times. The efficient design and analysis of these systems helps management in making better staffing decisions. This thesis aims to develop models for establishing agent staffing levels in organizations with cross-trained and specialized staff with a view to minimizing cost and maintaining a desirable customer satisfaction. The work investigates the effect of various traffic loads on the number of agents required and the cost. It also considers how using specialized agents, flexible agents and a combination of both categories of agents affects the system. It uses a contact centre that has agents with monolingual, bilingual and trilingual (English, French and Spanish) capabilities to do the study

MAXIMIZING THROUGHPUT USING DYNAMIC RESOURCE ALLOCATION AND DISCRETE EVENT SIMULATION

This research studies a serial two stage production system with two flexible servers which can be dynamically assigned to either station. This is modeled using discrete event simulation and more specifically the Arena software package by Rockwell. The goal is to determine dynamic allocation policies based upon the inventory level at each station to maximize the throughput of finished goods out of the system. This model adds to previous work by including actual switching time. The effect of the pre-emptive resume assumption is gauged, and the effectiveness of the OptQuest optimization package is also tested. Studies are conducted to determine the throughput of the system using easily implementable heuristics including when workers are together and separate. Additionally, the effect of buffer allocation and buffer sizing are studied, and it is shown that buffer allocation is not sensitive to changes in buffer ratio as long as there is buffer space available at each station while adding buffer space has a diminishing rate of return

On the Interface Between Operations and Human Resources Management

Operations management (OM) and human resources management (HRM) have historically been very separate fields. In practice, operations managers and human resource managers interact primarily on administrative issues regarding payroll and other matters. In academia, the two subjects are studied by separate communities of scholars publishing in disjoint sets of journals, drawing on mostly separate disciplinary foundations. Yet, operations and human resources are intimately related at a fundamental level. Operations are the context that often explains or moderates the effects of human resource activities such as pay, training, communications and staffing. Human responses to operations management systems often explain variations or anomalies that would otherwise be treated as randomness or error variance in traditional operations research models. In this paper, we probe the interface between operations and human resources by examining how human considerations affect classical OM results and how operational considerations affect classical HRM results. We then propose a unifying framework for identifying new research opportunities at the intersection of the two fields

Enabling flexibility through strategic management of complex engineering systems

”Flexibility is a highly desired attribute of many systems operating in changing or uncertain conditions. It is a common theme in complex systems to identify where flexibility is generated within a system and how to model the processes needed to maintain and sustain flexibility. The key research question that is addressed is: how do we create a new definition of workforce flexibility within a human-technology-artificial intelligence environment? Workforce flexibility is the management of organizational labor capacities and capabilities in operational environments using a broad and diffuse set of tools and approaches to mitigate system imbalances caused by uncertainties or changes. We establish a baseline reference for managers to use in choosing flexibility methods for specific applications and we determine the scope and effectiveness of these traditional flexibility methods. The unique contributions of this research are: a) a new definition of workforce flexibility for a human-technology work environment versus traditional definitions; b) using a system of systems (SoS) approach to create and sustain that flexibility; and c) applying a coordinating strategy for optimal workforce flexibility within the human- technology framework. This dissertation research fills the gap of how we can model flexibility using SoS engineering to show where flexibility emerges and what strategies a manager can use to manage flexibility within this technology construct”--Abstract, page iii

Throbbing Between Two Lives: Resource Pooling in Service Supply Chains

Resource pooling is known to benefit performance through reduced congestion, but primarily in settings with homogenous demand. In settings where demand is heterogeneous, pooling can be counter effective. The effects of pooling of staff when demand is heterogeneous and dependent are not known. We present a simulation model based on a service supply chain that delivers Interactive TV to customers. Customers expect high performance in terms of innovativeness and reliability. Based on the results of simulation analysis, we find that when target innovativeness of the service is increased, pooling outperforms not pooling, but the delays that are involved with pooling will make the system and hence its performance unstable. Stable and high performance can be realized through unbalanced hiring. This means that a target performance increase in the upstream stage of the chain (innovation), is accompanied by hiring staff in the downstream stages of the chain (QA and operation)

Modeling And Optimization Of Non-Profit Hospital Call Centers With Service Blending

This dissertation focuses on the operations problems in non-profit hospital call centers with inbound and outbound calls service blending. First, the routing policy for inbound and outbound calls is considered. The objective is to improve the system utilization under constraints of service quality and operators\u27 quantity. A collection of practical staffing assignment methods, separating and mixing staffing policy are evaluated. Erlang C queuing model is used to decide the minimum number of operators required by inbound calls. Theoretical analysis and numerical experiments illustrate that through dynamically assigning the inbound and outbound calls to operators under optimal threshold policy, mixing staffing policy is efficient to balance the system utilization and service quality. Numerical experiments based on real-life data demonstrate how this method can be applied in practice. Second, we study the staffing shift planning problem based on the inbound and outbound calls routing policies. A mathematical programming model is developed, based on a hospital call center with one kind of inbound calls and multiple kinds of outbound calls. The objective is to minimize the staffing numbers, by deciding the shift setting and workload allocation. The inbound calls service level and staffing utilization are taken into consideration in the constraints. Numerical experiments based on actual operational data are included. Results show that the model is effective to optimize the shift planning and hence reduce the call centers\u27 cost. Third, we model the staffing shift planning problem for a hospital call center with two kinds of service lines. Each kind of service is delivered through both inbound calls and outbound calls. The inbound calls can be transferred between these two service lines. A mathematical programming model is developed. The objective is to minimize the staffing cost, by deciding the shift setting and workload allocation. The inbound calls service level and staffing utilization are taken into consideration in the constraints. Numerical experiments are carried out based on actual operational data. Results show that the model is effective to reduce the call centers\u27 labor cost