The importance of cost optimization in fleet management for public institutions

Fleet managers are continuously challenged with determining the optimal equipment replacement time based on increasing operation costs and decreasing economic value. In addition, they are challenged with determining if a lease or purchase provides the greatest value. New technologies (e.g., electric vehicles) and governmental regulations can substantially alter and muddle the best course of action. Compounding upon these challenges, new equipment purchases and leases can create a negative perception among the general public. Therefore, there is a need for a literature review to analyze what information has previously been gathered to best understand whether a piece of equipment should be leased or purchased provided these regulations and new technologies. One important component of fleet management when looking at public institutions is the idea of cost optimization. Cost optimization allows for a continuous analysis of how public funds are being properly allocated and, in turn, where they can be saved. Cost optimization considers many factors, including public perception, where government agencies need the backing of the population that pays taxes to support their operations. The goal of this work is to research key factors and variables that influence the dynamics of cost optimization within the context of public sector fleet management. Some of these variables may include cost of ownership (economic value, salvage value, etc.) and operations (fuel, lubrication oil, tire selection and repair, etc.), technology integration, and stakeholder involvement. To begin, the researchers will collect data from the literature to determine the state of the practice around quantifiable approaches for optimal replacement time along with publicly available models, and various approaches to the lease-versus-buy decision. The literature review will further capture how public perception has historically been managed when new equipment purchase is necessary. By employing this conceptual model, the research aims to provide a comprehensive understanding of cost optimization in fleet management for public institutions. This model will help to create a methodical approach to investigating the different variables and provide recommendations to enhance cost-effective decisions in the management of fleets in public institutions while making sure the service to the general public is high-quality. Three core tasks will have been performed as part of this research (found in Figure 1). From the first task (literature review), the researchers expect to identify common impacts from the key factors (ownership and maintenance costs) and how they affect the overall budget, the growing impact of technology and savings provided from real-time data, any possible positive environmental impacts by reduced fuel consumption and emissions. From the second (survey) and third (interviews) tasks, it can be anticipated that information will be collected from entities indicating best practices and to allow for in-depth examination of historical data on their equipment fleets to develop the future tool. The discussions are likely to further increase the validity of the data collected, and ensure all topics were captured throughout the data collection process. The literature review is presented as part of this creative component and will examine current life-cycle analysis and equipment management practices. This literature review will capture the robust state of the practice with regard to the optimal equipment replacement time in a dynamic environment. This literature review examines the state of the practice for leased vehicle costs/valuation and evaluate models that consider changes in cost in order to provide a simple summary to LRRB members who have to make a lease-versus-buy decision. The survey and interview results are presented as part of this research, and include findings around topics such as driving factors and challenges in determining optimal replacement time, in actually making the replacement, and in determining between leasing and buying. Interviews will then be used to create a greater understanding of the data and to discuss various maintenance approaches and challenges. In addition, nonfinancial decision parameters will be discussed and lessons learned captured and presented

A hybrid methodology for optimal fleet management in an electric vehicle based flexible bus service

The ever-increasing traffic congestion and CO-{2} emission caused by rapid urbanization, calls for smarter and energy efficient transit services. Conventional public transit lacks the ability to meet these diversified needs. As a result, intelligent transit systems, influenced by the digital revolution have created a profound impact by enhancing the user-experience of transit services. Consequently, demand responsive transit (DRT) services, which operate with flexible routes and schedules have become a common option among commuters. Thus, in this work, we propose an electric vehicle (EV) based flexible bus service, a variant of DRT, that satisfies passenger demand in a given geographical zone. Next, we present a hybrid methodology to optimally manage the EV fleet minimizing the total vehicle miles travelled (VMT). Experimental results with a real map show that the proposed hybrid method achieves near-optimal results with 120x improvement in computation time. Further, the flexible bus service reduces VMT by over 70% in comparison to single occupancy vehicles, thus reducing both traffic congestion and CO-{2} emissions