Sustainable model integration of waste production and treatment process based on assessment of GHG

The paper presents a new model for supporting strategic decision-making in the area of municipal solid waste management. The effort is to integrate the assessment of greenhouse gas (GHG) to a sustainable economy. The goals are (in the following order) to reduce the waste produced, recycle at the highest rate as possible (material recovery) and to use the resultant residual waste for energy recovery. These features will be implemented through both pricing and advertising-like principles. The resulting mathematical model proposes multi-objective approach considering GHG and cost minimisation. The aim is to design the optimal waste management strategy, where stakeholders decide about the investment to the propagation of waste prevention and to advertising of waste recycling, and investors decide about new facility location and technological parameter. The availability of waste is projected in pricing method as well as the location of the facility. The mathematical model will utilise randomness in the form of waste production. All of the non-linearities (advertising and pricing) in the objective function will be replaced by piecewise linear approximation. The results of the work are applicable to the area of waste treatment infrastructure planning and to support decision-making at the micro-regional level with regard to the GHG impact. The original obtained solution will further be utilised for analyses dealing with all types of combustible waste. Copyright © 2018, AIDIC Servizi S.r.l

WS network design problem with nonlinear pricing solved by hybrid algorithm

The aim of the paper is to introduce a wait-and-see (WS) reformulation of the transportation network design problem with stochastic price-dependent demand. The demand is defined by hyperbolic dependency and its parameters are modeled by random variables. Then, a WS reformulation of the mixed integer nonlinear program (MINLP) is proposed. The obtained separable scenario-based model can be repeatedly solved as a finite set of MINLPs by means of integer programming techniques or some heuristics. However, the authors combine a traditional optimization algorithm and a suitable genetic algorithm to obtain a hybrid algorithm that is modified for theWS case. The implementation of this hybrid algorithm and test results, illustrated with figures, are also discussed in the paper. © Springer International Publishing AG 2016