Bi-level optimisation and machine learning in the management of large service-oriented field workforces.

The tactical planning problem for members of the service industry with large multi-skilled workforces is an important process that is often underlooked. It sits between the operational plan - which involves the actual allocation of members of the workforce to tasks - and the strategic plan where long term visions are set. An accurate tactical plan can have great benefits to service organisations and this is something we demonstrate in this work. Sitting where it does, it is made up of a mix of forecast and actual data, which can make effectively solving the problem difficult. In members of the service industry with large multi-skilled workforces it can often become a very large problem very quickly, as the number of decisions scale quickly with the number of elements within the plan. In this study, we first update and define the tactical planning problem to fit the process currently undertaken manually in practice. We then identify properties within the problem that identify it as a new candidate for the application of bi-level optimisation techniques. The tactical plan is defined in the context of a pair of leader-follower linked sub-models, which we show to be solvable to produce automated solutions to the tactical plan. We further identify the need for the use of machine learning techniques to effectively find solutions in practical applications, where limited detail is available in the data due to its forecast nature. We develop neural network models to solve this issue and show that they provide more accurate results than the current planners. Finally, we utilise them as a surrogate for the follower in the bi-level framework to provide real world applicable solutions to the tactical planning problem. The models developed in this work have already begun to be deployed in practice and are providing significant impact. This is along with identifying a new application area for bi-level modelling techniques

Measuring the Performance of Livability Programs, MTI Report 12-06

This report analyzes the performance measurement processes adopted by five large “livability” programs throughout the United States. It compares and contrasts these programs by examining existing research in performance measurement methods. The “best practices” of the examined performance measurement methods for each program are explored and analyzed with respect to their key characteristics. The report entails an appropriately comprehensive literature review of the current research on performance measurement methods from the perspective of various stakeholders including the public and government agencies. Additionally, the results of this literature review are used to examine the actual performance measures of the target programs from the perspective of different stakeholders. The goal of the report is to determine what did and did not work in these programs and their measurement methods, while making recommendations based on the results of the analysis for potential future programs

An Analytical Model To Assess Technology Needs In A Rural Community

Information technology (IT) has shaped fundamental changes throughout society. IT has facilitated the shift from an industrial age to a network age. In addition to altering commerce, education, government and communications, IT affects the construction of and response to social problems such as poverty and inequality. The very existence of the “digital divideâ€--â€--â€or lack of access to IT for certain segments of the population--â€--†is evidence of the ability of technology to worsen existing inequality. At the same time, technology promotes organizing efforts to disadvantaged communities, and it can connect people to a range of opportunities. The community technology movement--â€--â€a grassroots social movement that employs IT to empower historically disadvantaged individuals and communities--â€--â€demonstrates the potential of IT to serve as a tool of social change. In our research, we answer the following questions: What are the technological gaps that exist in low socioeconomic rural communities such as Vance County? And what are the community resources and potential partnerships specifically relevant to establishing a community technology center in rural communities such as those in Vance County? For this research, we created an analytical community--â€mapping model that collected, populated, organized and generated reliable data useful in determining the unmet technological needs of a rural community and producing an on--â€line or print “map†of the wide variety of relevant technology literacy activities and public access sites in a low socioeconomic rural community. The overall approach to this research was that of mixed methods. The proposed model consisted of a needs assessment that included a proven survey (that we modified for Vance County), interview questions, a case study, and evaluation research that will aid communities in discovering what digital technologies are currently available, and to whom. Judging from our data, we concluded that Vance County has several organizations that serve underserved populations. However, there is a gap in computer literacy service to youth in the community, and there are no organizations that use their computers solely for computer literacy training. Our findings also reveal that Vance County community technology efforts are fragmented and the community’s efforts in this area are not visible to the community nor are their linkages among them. Finally, as a result of our data, we were not able to produce an effect map of relevant technology literacy activities in Vance County, as there were no activities or programs to report. Our recommendations, as a result of our research are as follows: 1) To submit a proposal to the policy makers of the city of Henderson to include community technology into their economic and community development policy goals. 2) To propose a Community Technology Planner position to the City Council. 3) To create a community forum to discuss community technology needs in Vance County

An Analytical Model To Assess Technology Needs In A Rural Community

Information technology (IT) has shaped fundamental changes throughout society. IT has facilitated the shift from an industrial age to a network age. In addition to altering commerce, education, government and communications, IT affects the construction of and response to social problems such as poverty and inequality. The very existence of the “digital divideâ€--â€--â€or lack of access to IT for certain segments of the population--â€--†is evidence of the ability of technology to worsen existing inequality. At the same time, technology promotes organizing efforts to disadvantaged communities, and it can connect people to a range of opportunities. The community technology movement--â€--â€a grassroots social movement that employs IT to empower historically disadvantaged individuals and communities--â€--â€demonstrates the potential of IT to serve as a tool of social change. In our research, we answer the following questions: What are the technological gaps that exist in low socioeconomic rural communities such as Vance County? And what are the community resources and potential partnerships specifically relevant to establishing a community technology center in rural communities such as those in Vance County? For this research, we created an analytical community--â€mapping model that collected, populated, organized and generated reliable data useful in determining the unmet technological needs of a rural community and producing an on--â€line or print “map†of the wide variety of relevant technology literacy activities and public access sites in a low socioeconomic rural community. The overall approach to this research was that of mixed methods. The proposed model consisted of a needs assessment that included a proven survey (that we modified for Vance County), interview questions, a case study, and evaluation research that will aid communities in discovering what digital technologies are currently available, and to whom. Judging from our data, we concluded that Vance County has several organizations that serve underserved populations. However, there is a gap in computer literacy service to youth in the community, and there are no organizations that use their computers solely for computer literacy training. Our findings also reveal that Vance County community technology efforts are fragmented and the community’s efforts in this area are not visible to the community nor are their linkages among them. Finally, as a result of our data, we were not able to produce an effect map of relevant technology literacy activities in Vance County, as there were no activities or programs to report. Our recommendations, as a result of our research are as follows: 1) To submit a proposal to the policy makers of the city of Henderson to include community technology into their economic and community development policy goals. 2) To propose a Community Technology Planner position to the City Council. 3) To create a community forum to discuss community technology needs in Vance County

A multi-objective genetic type-2 fuzzy logic based system for mobile field workforce area optimization

In industries which employ large numbers of mobile field engineers (resources), there is a need to optimize the task allocation process. This particularly applies to utility companies such as electricity, gas and water suppliers as well as telecommunications. The process of allocating tasks to engineers involves finding the optimum area for each engineer to operate within where the locations available to the engineers depends on the work area she/he is assigned to. This particular process is termed as work area optimization and it is a sub-domain of workforce optimization. The optimization of resource scheduling, specifically the work area in this instance, in large businesses can have a noticeable impact on business costs, revenues and customer satisfaction. In previous attempts to tackle workforce optimization in real world scenarios, single objective optimization algorithms employing crisp logic were employed. The problem is that there are usually many objectives that need to be satisfied and hence multi-objective based optimization methods will be more suitable. Type-2 fuzzy logic systems could also be employed as they are able to handle the high level of uncertainties associated with the dynamic and changing real world workforce optimization and scheduling problems. This paper presents a novel multi-objective genetic type-2 fuzzy logic based system for mobile field workforce area optimization, which was employed in real world scheduling problems. This system had to overcome challenges, like how working areas were constructed, how teams were generated for each new area and how to realistically evaluate the newly suggested working areas. These problems were overcome by a novel neighborhood based clustering algorithm, sorting team members by skill, location and effect, and by creating an evaluation simulation that could accurately assess working areas by simulating one day's worth of work, for each engineer in the working area, while taking into account uncertainties. The results show strong improvements when the proposed system was applied to the work area optimization problem, compared to the heuristic or type-1 single objective optimization of the work area. Such optimization improvements of the working areas will result in better utilization of the mobile field workforce in utilities and telecommunications companies

Cross-trained workforce planning models

Cross-training has emerged as an effective method for increasing workforce flexibility in the face of uncertain demand. Despite recently receiving substantial attention in workforce planning literature, a number of challenges towards making the best use of cross-training remain. Most notably, approaches to automating the allocation of workers to their skills are typically not scalable to industrial sized problems. Secondly, insights into the nature of valuable cross-training actions are restricted to a small set of predefined structures. This thesis develops a multi-period cross-trained workforce planning model with temporal demand flexibility. Temporal demand flexibility enables the flow of incomplete work (or carryover ) across the planning horizon to be modelled, as well as an the option to utilise spare capacity by completing some work early. Set in a proposed Aggregate Planning stage, the model permits the planning of large and complex workforces over a horizon of many months and provides a bridge between the traditional Tactical and Operational stages of workforce planning. The performance of the different levels of planning flexibility the model offers is evaluated in an industry motivated case study. An extensive numerical study, under various supply and demand characteristics, leads to an evaluation of the value of cross-training as a supply strategy in this domain. The problem of effectively staffing a pre-fixed training structure (such as the modified chain or block) is an aspect of cross-training which has been extensively studied in the literature. In this thesis, we attempt to address the more frequently faced problem of ‘how should we train our existing workforce to improve demand coverage?’. We propose a two-stage stochastic programming model which extends existing literature by allowing the structure of cross-training to vary freely. The benefit of the resulting targeted training solutions are shown in application using a case study provided by BT. A wider numerical study highlights ‘rules-of-thumb’ for effective training solutions under a variety of characteristics for uncertain demand

Generic Continuity of Operations/Continuity of Government Plan for State-Level Transportation Agencies, Research Report 11-01

The Homeland Security Presidential Directive 20 (HSPD-20) requires all local, state, tribal and territorial government agencies, and private sector owners of critical infrastructure and key resources (CI/KR) to create a Continuity of Operations/Continuity of Government Plan (COOP/COG). There is planning and training guidance for generic transportation agency COOP/COG work, and the Transportation Research Board has offered guidance for transportation organizations. However, the special concerns of the state-level transportation agency’s (State DOT’s) plan development are not included, notably the responsibilities for the entire State Highway System and the responsibility to support specific essential functions related to the State DOT Director’s role in the Governor’s cabinet. There is also no guidance on where the COOP/COG planning and organizing fits into the National Incident Management System (NIMS) at the local or state-level department or agency. This report covers the research conducted to determine how to integrate COOP/COG into the overall NIMS approach to emergency management, including a connection between the emergency operations center (EOC) and the COOP/COG activity. The first section is a presentation of the research and its findings and analysis. The second section provides training for the EOC staff of a state-level transportation agency, using a hybrid model of FEMA’s ICS and ESF approaches, including a complete set of EOC position checklists, and other training support material. The third section provides training for the COOP/COG Branch staff of a state-level transportation agency, including a set of personnel position descriptions for the COOP/COG Branch members

Compilation of thesis abstracts, September 2009

NPS Class of September 2009This quarter’s Compilation of Abstracts summarizes cutting-edge, security-related research conducted by NPS students and presented as theses, dissertations, and capstone reports. Each expands knowledge in its field.http://archive.org/details/compilationofsis109452751