Subregion Districting Analysis for Municipal Solid Waste Collection Privatization

Privatization of municipal solid waste (MSW) collection can improve service quality and reduce cost. To reduce the risk of an incapable company serving an entire collection area and to establish a competitive market, a large collection area should be divided into two or more sub-regions, with each s...

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Bibliographic Details
Published in:Journal of the Air & Waste Management Association (1995) 2008-01, Vol.58 (1), p.104-111
Main Authors: Lin, Hung-Yueh, Kao, Jehng-Jung
Format: Article
Language:English
Subjects:
Access control
Applied sciences
Cities
Collection services
Competition
Contracts
Costs and Cost Analysis
Efficiency, Organizational
Evaluation
Exact sciences and technology
Integer programming
Models, Theoretical
Municipal solid waste
Planning
Pollution
Privatization
Privatization - economics
Refuse collection
Refuse Disposal - economics
Refuse Disposal - methods
Refuse disposal industry
Sales territories
Service enhancement
Studies
Taiwan
Transportation
Urban and domestic wastes
Wastes
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Summary:Privatization of municipal solid waste (MSW) collection can improve service quality and reduce cost. To reduce the risk of an incapable company serving an entire collection area and to establish a competitive market, a large collection area should be divided into two or more sub-regions, with each sub-region served by a different company. The MSW sub-region districting is generally done manually, based on the planner's intuition. Major drawbacks of a manual approach include the creation of a districting plan with poor road network integrity for which it is difficult to design an efficient collection route. The other drawbacks are difficulty in finding the optimal districting plan and the lack of a way to consistently measure the differences among sub-regions to avoid unfair competition. To determine an MSW collection sub-region districting plan, this study presents a mixed-integer optimization model that incorporates factors such as compactness, road network integrity, collection cost, and regional proximity. Two cases are presented to demonstrate the applicability of the proposed model. In both cases, districting plans with good road network integrity and regional proximity have been generated successfully.
ISSN:1096-2247
2162-2906
DOI:10.3155/1047-3289.58.1.104