Case Study: Bus Fleet Replacement

Abstract

Parallel replacement analysis is concerned with determining minimum cost replacement schedules for a group of assets that are economically interdependent and operate in parallel. That is, keep and replace decisions are required for each asset among a group of assets over a specified horizon. The assets are economically linked through economies of scale or budgeting constraints. One application of parallel replacement analysis is fleet replacement. We recently studied the operations, including fleet replacement policies, for a city transit bus operator in Europe. Key factors in their replacement decisions included the ability to choose from multiple manufacturers, purchase price, and government regulations. We explore these and other factors, by solving a heterogeneous replacement problem with fixed costs, budgeting constraints, and demand constraints.Through extensive sensitivity analysis we analyze the impact of various parameters on decisions, in terms of the choice of replacement assets, as well as the optimal time to retain assets. Additionally, we provide motivation for future research in this application area, which is important for many cities.

Off-Line and User-Oriented Approach for Supplier Selection in Dynamic Environment: A Case Study in the Healthcare Services

“…Liao and Rittscher [20] suggest a genetic model designed to enhance supplier flexibility in the supplier selection process given normally distributed random demand and capacity constraints with the acceptable assumption that such enhancement would contribute to greater flexibility throughout the supply chain. In a case study of replacing the bus fleet of a large organization, Keles and Hartman [21] used an MIP model and sensitivity analysis to obtain an optimal solution for dynamic business environment changes. The objective of this study was to determine optimal long-term timetables for replacing the old bus fleet, with several manufacturers submitting proposals.…”

An integrated econometric model for bus replacement and determination of reserve fleet size based on predictive maintenance

“…In the road transport sector, the efficient use of assets is linked to a well-structured policy of fleet evaluation and replacement. Some cases of fleet replacement applied to urban buses are reported in [10,19,25,30,40,43,45,51,55]. Beichelt [10] proposes a policy for optimal scheduling replacement intervals of technical systems on the basis of a maintenance cost parameter: a system is replaced by a new one as soon as the maintenance cost within a replacement cycle reaches or exceeds a given level.…”

“…Franck et al [25] describe an industrial application of a Power Law Process (PLP) and a theoretical replacement model. Pinar and Hartman [40] adopt a model for a transit fleet replacement problem with multiple types of buses. However, many cost functions are highly simplified or not based on real data, and the authors do not study the variability in vehicular characteristics, usages, and market fluctuations.…”

Time replacement optimization model: comparative analysis of urban transport fleets using Monte Carlo Simulation

“…For fleet replacement, the literature suggests two kinds of models: economic engineering (EE) and operational research (OR) models [12,16]. EE models are restricted to economic and financial aspects, with technological, management and strategic variables considered as exogenous.…”