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Optimization models for clustering of solid waste collection process

Abbas Al‐Refaie, Ahmad Al-Hawadi, Saja Fraij

2020Engineering Optimization28 citationsDOI

Abstract

In Jordan, the waste collection process incurs high transportation and operation costs. The main reasons for the high transportation costs are inefficient clustering and poor routing systems. In response, this research proposes a mathematical model for optimal clustering of garbage containers or bins (referred to as customers) for solid waste collection. The model’s objective function is to define the customers of each cluster such that the transportation costs within each cluster and between the hubs and depots are minimized, and the satisfaction of the clusters’ demand mean and variance is maximized. The optimization model was illustrated on solid waste collection for 20 customers, where the results showed that the proposed model is found to be effective in optimizing the waste collection process. In practice, this approach can be utilized in waste management for planning waste collection processes with minimal transportation costs while maximizing operational capacity.

Topics & Concepts

Cluster analysisWaste collectionData collectionVehicle routing problemProcess (computing)Municipal solid wasteOperations researchVariance (accounting)GarbageFunction (biology)Garbage collectionComputer scienceRouting (electronic design automation)EngineeringMathematical optimizationWaste managementBusinessMathematicsMachine learningStatisticsOperating systemAccountingBiologyComputer networkEvolutionary biologyMunicipal Solid Waste ManagementVehicle Routing Optimization MethodsUrban and Freight Transport Logistics
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