“…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).…”