Measuring Incineration Plants' Performance using Combined Data Envelopment Analysis, Goal Programming and Mixed Integer Linear Programming

Konstantinos Petridis, Prasanta K Dey

Research output: Contribution to journalArticle

Abstract

Incineration plants produce heat and power from waste, reduce waste disposal to landfills, and discharge harmful emissions and bottom ash. The objective of the incineration plant is to maximize desirable outputs (heat and power) and minimize undesirable outputs (emissions and bottom ash). Therefore, studying the overall impact of incineration plants in a region so as to maximize the benefits and minimize the environmental impact is significant. Majority of prior works focus on plant specific decision making issues including performance analysis. This study proposes a hybrid Data Envelopment Analysis (DEA), Goal Programming (GP) and Mixed Integer Linear Programming (MILP) model to assess the performance of incineration plants, in a specific region, to enhance overall power production, consumption of waste and reduction of emissions. This model not only helps the plant operators to evaluate the effectiveness of incineration but also facilitates the policy makers to plan for overall waste management of the region through decision-making on adding and closing plants on the basis of their efficiency. Majority of prior studies on incineration plants emphasize on how to improve their performance on heat and power production and neglect the waste management aspects. Additionally, optimizing benefits and minimizing negative outputs through fixing targets in order to make decision on shutting down the suboptimal plants has not been modeled in prior research. This research combines both the aspects and addresses the overall performance enhancement of incineration plants within a region from both policy makers and plant operators’ perspectives. The proposed combined DEA, GP and MILP model enables to optimize incineration plants performance within a region by deriving efficiency of each plant and identifying plants to close down on the basis of their performance. The proposed model has been applied to a group of 22 incineration plants in the UK using secondary data in order to demonstrate the effectiveness of the model. .
Original languageEnglish
Pages (from-to)467–491
JournalAnnals of Operations Research
Volume267
Issue number1-2
Early online date3 Apr 2018
DOIs
Publication statusPublished - 1 Aug 2018

Fingerprint

Incineration
Goal programming
Data envelopment analysis
Plant performance
Mixed integer linear programming
Operator
Politicians
Decision making
Waste management
Performance analysis
Secondary data
Plant closings
Enhancement
Neglect
Undesirable outputs
Waste disposal
Landfill
Environmental impact
Make-to-order

Bibliographical note

© The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Keywords

  • Incineration plants
  • DEA
  • Goal Programming
  • MILP
  • Waste to Energy

Cite this

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abstract = "Incineration plants produce heat and power from waste, reduce waste disposal to landfills, and discharge harmful emissions and bottom ash. The objective of the incineration plant is to maximize desirable outputs (heat and power) and minimize undesirable outputs (emissions and bottom ash). Therefore, studying the overall impact of incineration plants in a region so as to maximize the benefits and minimize the environmental impact is significant. Majority of prior works focus on plant specific decision making issues including performance analysis. This study proposes a hybrid Data Envelopment Analysis (DEA), Goal Programming (GP) and Mixed Integer Linear Programming (MILP) model to assess the performance of incineration plants, in a specific region, to enhance overall power production, consumption of waste and reduction of emissions. This model not only helps the plant operators to evaluate the effectiveness of incineration but also facilitates the policy makers to plan for overall waste management of the region through decision-making on adding and closing plants on the basis of their efficiency. Majority of prior studies on incineration plants emphasize on how to improve their performance on heat and power production and neglect the waste management aspects. Additionally, optimizing benefits and minimizing negative outputs through fixing targets in order to make decision on shutting down the suboptimal plants has not been modeled in prior research. This research combines both the aspects and addresses the overall performance enhancement of incineration plants within a region from both policy makers and plant operators’ perspectives. The proposed combined DEA, GP and MILP model enables to optimize incineration plants performance within a region by deriving efficiency of each plant and identifying plants to close down on the basis of their performance. The proposed model has been applied to a group of 22 incineration plants in the UK using secondary data in order to demonstrate the effectiveness of the model. .",
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Measuring Incineration Plants' Performance using Combined Data Envelopment Analysis, Goal Programming and Mixed Integer Linear Programming. / Petridis, Konstantinos; Dey, Prasanta K.

In: Annals of Operations Research, Vol. 267, No. 1-2, 01.08.2018, p. 467–491.

Research output: Contribution to journalArticle

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