The spread of COVID-19 and similar viruses poses new challenges for our society. There is a strong incentive towards safety measures that help to mitigate the outbreaks. Many countries have imposed social distancing measures that require a minimum distance between people in given places, such as schools, restaurants, shops, etc. This in turn creates complications for these places, as their function is to serve as many people as they were originally designed for. In this paper, we pose the problem of using the available space in a given place, such that the social distancing measures are satisfied, as a p-dispersion problem. We use recent algorithmic advancements, that were developed for the p-dispersion problem, and combine them with discretization schemes to find computationally attainable solutions to the p-dispersion problem and investigate the trade-off between the level of discretization and computational efforts on one side, and the value of the optimal solution on the other.
The paper presents a new model for integration of circular economy strategies into the municipal solid waste management. The goals are to reduce the waste produced, recycle at the highest rate as possible (material recovery) and to use the resultant residual waste for energy recovery. Such a strategy utilizes both pricing and advertising principles in the mixed integer linear programming model while accounting two criterions-assessment of greenhouse gas (GHG) and cost minimization. The aim is to design the optimal waste management grid to suggest a sustainable economy with environmental concerns. The government, municipalities and/or authorized packaging company decide about the investments to the propagation of waste prevention and to advertising of waste recycling, while investors decide about new facility location and technological parameter. The availability of waste is projected in pricing method as well as in the location of the facility. The mathematical model will consider randomness in the form of waste production. The suggested non-linear functions of pricing and advertising are replaced by piecewise linear approximation to reduce computational complexity. The proposed multi-objective model is applied in a case study for the Czech Republic in the area of waste treatment infrastructure planning to support decision-making at the micro-regional level. The integration of circular economy principles, considering also the total amount of produced GHG, revealed the existing potential in waste prevention. On the other hand, the increase of recycling is limited, landfills are not supported and the energy recovery is preferred. However, the planning of the complex system relies on the decision-maker.
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