As maintenance and operation costs increase with usage over time, equipment is replaced when the value of new equipment is more attractive. Some methods have been developed to solve this problem. In the public transport sector, such problems are frequently analyzed by fleet managers and determined by bus age restriction regulations. We propose an Integer Programming model that integrates both budgetary and environmental constraints (CO₂ emissions) which, as far as we know, have not previously been studied in conjunction. The study aims to determine the optimal replacement plan for a fleet of diesel buses of different size, age, maintenance costs and emissions rates, with new (less polluting) diesel buses over a time horizon of 50 years. The results indicate that it is possible to reduce emissions with a low annual budget using an optimal replacement policy.

This paper presents a multiobjective optimization model to find efficient bus fleet combinations taking into account greenhouse gas emissions, conventional air pollutant emissions and costs. The goal is to minimize, simultaneously, three objective functions, Z₁ (CO₂ emissions), Z₂ (Other Types of Emissions), and Z₃ (total costs), for a buses fleet of a transit agency. For this case, there were four types of buses (diesel, electric bus, electric bus of fast charging, and CNG (compressed natural gas bus), which were analyzed in three different lines (South-North, Itinga, and South-Central) in Joinville city, Brazil. The respective data were modeled and optimized using MS Excel. Two different scalarization methods (the Weighted Tchebycheff and the Augmented Weighted Tchebycheff) are used for solving this buses fleet management problem. Different tradeoffs, in terms of the objectives, were obtained. The choice of a bus type is directly related to the characteristics (number of stops, average speed among others) of each line. The electrical bus is the best choice for reducing emissions but has a high initial cost and low autonomy. The results indicate that in the South–North line due to the large number of stops and low average speed, the electric bus is the type of dominant. In the other lines, the dominant ones were the diesel bus in the Itinga line and the CNG bus in the South line.

This paper deals with the problem of estimation maintenance costs for the case of the pitch controls system of wind farms turbines. Previous investigations have estimated these costs as (traditional) “crisp” values, simply ignoring the uncertainty nature of data and information available. This paper purposes an extended version of the estimation model by making use of the Fuzzy Set Theory. The results alert decision-makers to consequent uncertainty of the estimations along with their overall level, thus improving the information given to the mainte-nance support system.