Nowadays, in the European Union selective solid waste management be-longs to important responsibilities of municipalities. In Solid Waste Management (SWM) the main operational task is to set a schedule for solid waste collection and to find optimal routes for garbage trucks so that the total costs of solid waste collection service can be minimized subject to a series of constraints which guarantee not only fulfillment of SWM’s obligations but also desirable level of quality of that service. Optimization problem of garbage trucks routing is a special case of rich Vehicle Routing Problem as it has to cover following constraints: pickup nodes (clients) must be visited during their predefined time windows; the number and capacity of depots and specialized sorting units can-not be exceeded; each garbage truck can be assigned to at most one depot; each route should be dedicated to collecting one type of segregated solid waste, and the route must be served by a garbage truck which can collect that type of solid waste; availability of garbage trucks and their drivers must be respected; each garbage truck must be drained at a specialized sorting unit before going back to the depot. This paper contributes with a new Mixed-Integer Programming (MIP) model for the Selective Solid Waste Collection Routing Problem (SS-WCRP) with time windows, limited heterogeneous fleet, and different types of segregated solid waste to be collected separately. Utilization of MIP for solving small-sized instance of the Fleet Optimization Problem for Selective Solid Waste Collection (FOPSSWC) is and obtained results are reported.

Nowadays, robust and efficient solid waste collection is crucial to motivate citizens to participate in the circular economy by sorting recyclable solid waste. Vocational vehicles, including garbage trucks, contribute significantly to CO2 emissions; therefore, it is strongly recommended, and in the European Union it is mandatory, to replace conventional-fuel-based garbage trucks with electric ones. For providing sustainable and energy-efficient solid waste collection with a heterogeneous fleet, in-depth mathematical computations are needed to support solving complex decision-making problems, including crew rostering and vehicle routing, because the distance and capacity of electric garbage trucks differ from conventional-fuel-based ones. However, the literature on solid waste collection using electric garbage trucks is still relatively scarce. The main contribution of this paper is developing an optimization problem for balancing travel distance assigned to each garbage truck of a heterogeneous fleet. The problem is based on specific requirements of the Municipal Solid Waste Management in Cracow, Poland, where the working time of routes is balanced and the total time of collection service can be minimized. For the problem, an MIP program was developed to generate optimal crew schedules, so that the hitherto network of segregated solid waste pickup nodes can be served using a heterogeneous fleet in which the share of electric garbage trucks is up to 30%. We study the impact of the changed composition of the fleet on modifications in crew rostering due to the shorter range of an electric vehicle compared to a conventional-fuel-based one.

There are numerous ways of organizing the municipal solid waste collection system. For instance, separate collection of segregated recyclable solid waste can be based on a network of pickup points equipped with big recycling bins (BRB) to which citizens have unlimited access. The key to motivate citizens to use these bins is to provide a robust and efficient system of emptying them. The schedule of segregated solid waste collection from BRBs in Krakow municipality is prepared by decision-makers using manual tools, and there is a need for tools supporting decision-making, as solid waste management is getting more and more complicated due to laws and regulations. In this paper, the Vehicle Routing Problem (VRP) for segregated solid waste collection from BRBs is solved using Large Neighborhood Search algorithm implemented in the VRP Spreadsheet Solver and illustrated with a case study based on selective recyclables collection from BRBs in Krakow municipality. The real SWM system was adapted for requirements of the VRP Spreadsheet Solver, and obtained results were compared with the requirements of the garbage trucks routing problem in Krakow municipality.

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