A stochastic optimization framework for planning of waste collection and value recovery operations in smart and sustainable cities
作者： Parth Jatinkumar Shah , Theodoros Anagnostopoulos , Arkady Zaslavsky , Sara Behdad
DOI: 10.1016/J.WASMAN.2018.05.019
关键词: Data acquisition 、 Truck 、 Waste collection 、 Smart city 、 Stochastic optimization 、 Value (economics) 、 Computer science 、 Energy consumption 、 Quality (business) 、 Operations research
摘要: The concept of City 2.0 or smart city is offering new opportunities for handling waste management practices. existing studies have started addressing problems in cities mainly by focusing on the design sensor-based Internet Things (IoT) technologies, and optimizing routes collection trucks with aim minimizing operational costs, energy consumption transportation pollution emissions. In this study, importance value recovery from trash bins highlighted. A stochastic optimization model based chance-constrained programming developed to optimize planning operations. objective proposed minimize total cost while maximizing still embedded bins. collected modeled as an uncertain parameter reflect that can be recovered each bin due condition quality waste. application shown using a numerical example. study opens venues incorporating aspect into development data acquisition technologies enable municipalities monitor mix recyclables individual
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