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Estimating Transportation Costs and Emissions of Recyclables in Rhode Island Municipalities Using a GIS, Routing Machine, and Genetic Algorithm.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Estimating Transportation Costs and Emissions of Recyclables in Rhode Island Municipalities Using a GIS, Routing Machine, and Genetic Algorithm./
作者:	Martin-Jourdenais, Luke Norman.
面頁冊數:	1 online resource (245 pages)
附註:	Source: Masters Abstracts International, Volume: 84-03.
Contained By:	Masters Abstracts International84-03.
標題:	Industrial engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29259276click for full text (PQDT)
ISBN:	9798351410104

Estimating Transportation Costs and Emissions of Recyclables in Rhode Island Municipalities Using a GIS, Routing Machine, and Genetic Algorithm.
Martin-Jourdenais, Luke Norman.

Estimating Transportation Costs and Emissions of Recyclables in Rhode Island Municipalities Using a GIS, Routing Machine, and Genetic Algorithm. - 1 online resource (245 pages)

Source: Masters Abstracts International, Volume: 84-03.

Thesis (M.S.)--University of Rhode Island, 2022.

Includes bibliographical references

Transportation and logistics of recyclable materials are major cost drivers within recycling systems. In low and medium income countries, the collection costs of municipal solid waste (MSW) respectively can take up to 80-90% and 50-80% of the municipal solid waste management budget. Reducing these costs can significantly improve the viability of recycling systems. A promising approach for cost reduction in this context is improved routing of refuse vehicles, which can be done by developing and using advanced mathematical optimization algorithms and data information systems. Within the optimization research field, vehicle routing is addressed within the capacitated vehicle routing problem (CVRP). The objective is to minimize the total cost of a fleet of vehicles with a designated capacity. The CVRP is stated as an NP-Hard problem in combinatorial optimization problems meaning there is no known algorithm to solve these types of problems within polynomial time. Various heuristics are used to solve the CVRP and this study aims to use a genetic algorithm. The genetic algorithm provides feasible results to the CVRP within reasonable time. Applying the CVRP to a real-world instance requires road network distances compared to euclidean distances. In this thesis, a CVRP is solved using data processed in a geographical information system (GIS), existing local government databases, a routing machine, and a genetic algorithm to estimate recycling costs and emissions for municipalities in the state of Rhode Island.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798351410104Subjects--Topical Terms:

526216
Industrial engineering.
Subjects--Index Terms:

Transportation costsIndex Terms--Genre/Form:

542853
Electronic books.

Estimating Transportation Costs and Emissions of Recyclables in Rhode Island Municipalities Using a GIS, Routing Machine, and Genetic Algorithm.
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504 $a Includes bibliographical references
520 $a Transportation and logistics of recyclable materials are major cost drivers within recycling systems. In low and medium income countries, the collection costs of municipal solid waste (MSW) respectively can take up to 80-90% and 50-80% of the municipal solid waste management budget. Reducing these costs can significantly improve the viability of recycling systems. A promising approach for cost reduction in this context is improved routing of refuse vehicles, which can be done by developing and using advanced mathematical optimization algorithms and data information systems. Within the optimization research field, vehicle routing is addressed within the capacitated vehicle routing problem (CVRP). The objective is to minimize the total cost of a fleet of vehicles with a designated capacity. The CVRP is stated as an NP-Hard problem in combinatorial optimization problems meaning there is no known algorithm to solve these types of problems within polynomial time. Various heuristics are used to solve the CVRP and this study aims to use a genetic algorithm. The genetic algorithm provides feasible results to the CVRP within reasonable time. Applying the CVRP to a real-world instance requires road network distances compared to euclidean distances. In this thesis, a CVRP is solved using data processed in a geographical information system (GIS), existing local government databases, a routing machine, and a genetic algorithm to estimate recycling costs and emissions for municipalities in the state of Rhode Island.
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