An optimization model for bus fleet replacement with budgetary and environmental constraints

Maintenance and sustainability: a systematic review of modeling-based literature

“…For example, capital replacement decisions will be short-sighted if they are based only on economic considerations. This is highlighted in the works of Ali et al (2012) for taxi fleet replacement, Emiliano et al (2020) for bus fleet replacement, Taghipour and Salari (2015) for vehicles replacement, among others. All these authors accounted for environmental and/or social aspects in replacement decision-making alongside economic considerations.…”

“…This optimal replacement policy has been developed using dynamic programming to minimize both economic and emission related costs over a finite planning horizon. Similarly, both environmental and budgetary constraints have been considered by Emiliano et al (2020) in their integer programming model for bus fleet replacement. The developed model has been applied in a case study for a Brazilian city where the aim is to determine the optimal replacement plan, over a time horizon of 50 years, for 91 buses with different ages, sizes, maintenance costs and emission rates.…”

“…This optimal replacement policy has been developed using dynamic programming to minimize both economic and emission related costs over a finite planning horizon. Similarly, both environmental and budgetary constraints have been considered by Emiliano et al. (2020) in their integer programming model for bus fleet replacement.…”

“…This is highlighted in the works of Ali et al. (2012) for taxi fleet replacement, Emiliano et al. (2020) for bus fleet replacement, Taghipour and Salari (2015) for vehicles replacement, among others.…”

Strategic vehicle fleet management–a joint solution of make-or-buy, composition and replacement problems

“…One of the chronologically first types of optimization methods applied to fleet management problems was linear (including integer, mixed integer and binary) mathematical programming – LP. There are numerous and diverse applications of the LP to the fleet management including the following: the fleet sizing problem – FSP (Dantzig and Fulkerson, 1954; Kirby, 1959; Wyatt, 1961; Mole, 1975; Ceder and Stern, 1981; List et al , 2003 – a bi-objective, stochastic model solved with a robust optimization technique; Balac et al , 2020 – a mixed-integer linear programming (MILP) applied to a fleet of pooled automated vehicles, AVs; Zhang et al , 2020 – an MILP applied to a fleet of autonomous electric vehicles, AEVs); the fleet composition problem – FCP (Gould, 1969; Mole, 1975; Etezadi and Beasley, 1983; Bojovic et al , 2010 – problem solved with the Fuzzy Analytic Hierarchy Process method); the replacement problem – RP (Suzuki and Pautsch, 2005; Figliozzi et al , 2011; Boudart and Figliozzi, 2012; Parthanadee et al , 2012; Li et al , 2015; Buyuktahtakin and Hartman, 2016 – an MIP formulation of the parallel RP under economies of scale and technological change; Ngo et al , 2018 – an integer linear programming (ILP) model solved using a branch-and-bound algorithm; Emiliano et al , 2020 – an integer programming model integrating both budgetary and environmental constraints); the vehicle assignment problem – VAP (Rushmeier et al , 1997; Ziarati et al , 1999 – problem solved with a customized branch-and-cut algorithm); the vehicle routing problem – VRP (Taillard, 1999 – HFFVRP); the mixed FCP/VRP (Golden et al , 1984 – FSMVRP; Vis et al , 2005 – FSMVRPTW solved with simulation) and the make-or-buy problem – MoB (Klincewicz et al , 1990; Stojanovic et al , 2011).…”