Strategic plans for waste management require information on the current and future waste generation as a primary data source. Over the years, various approaches and methods for waste generation modeling have been presented and applied. This review provides a summary of the tasks that require information on waste generation that are most frequently handled in waste management. It is hypothesized that there is not currently a modeling approach universally suitable for forecasting any fraction of waste. It is also hypothesized that most models do not allow for modeling different scenarios of future development. Almost 360 publications were examined in detail, and all of the tracked attributes are included in the supplementary. A general step-by-step guide to waste generation forecasting, comprising data preparation, pre-processing, processing, and post-processing, was proposed. The problems that occurred in the individual steps were specified, and the authors’ recommendations for their solution were provided. A forecasting approach based on a short time series is presented, due to insufficient options of approaches for this problem. An approach is presented for creating projections of waste generation depending on the expected system changes. Researchers and stakeholders can use this document as a supporting material when deciding on a suitable approach to waste generation modeling or waste management plans.

Waste management is still an expanding eld which needs to be constantly enhanced so that waste transportation and treatment is as eective as possible. An important part of this process is a waste collection at the municipal level. Decision-making about daily routing for all vehicles from a heterogenous eet substantially in uences the expenses of technical services. The need of route scheduling comes also from the newly separated fractions. Transportation features include the capacity of vehicles, number and type of containers on the route, traffic light delays and many others. The mathematical model that properly describes the real practice of servicing containers has not been published yet. Moreover, routing problemsare generally not solvable by exact methods, so the appropriate heuristic algorithm has been developed. A case study with obtained results is discussed. This solution serves not only to improve the current operational situation, but also to create new route schedules for increasing number of collected commodities.