A decomposition algorithm for organic solid waste supply chain optimization under uncertainty

Yousef Saif; Muhammed Rizwan; Ali Almansoori; Ali ElKamel

doi:10.1016/j.egypro.2019.01.982

A decomposition algorithm for organic solid waste supply chain optimization under uncertainty

Yousef Saif, Muhammed Rizwan, Ali Almansoori, Ali ElKamel

Chemical and Petroleum Engineering

Research output: Contribution to journal › Conference article › peer-review

6 Scopus citations

Abstract

Storage of municipality solid waste (MSW) in landfills is a common practice of the past. Negative impacts of landfills have motivated interest in the sustainable utilization of MSW. In this study, we cover the treatment of the organic MSW supply chain problem. The supply chain network is composed by several arcs connecting sources of organic MSW by treatment facilities, and markets imposing demand for power. A two-stage stochastic MILP model is formulated to examine the effects of the supply-demand, and power price uncertainties. The first stage decision variables involve technology and capacity selection. The second stage decision variables deal with transportation, and power production. The main contribution of the research study is the application of an L-shaped decomposition algorithm to solve a large scale organic MSW supply chain model under uncertainty. Another contribution is the application of a minmax regret risk model to analyze the financial risk in the organic MSW supply chain problem. A case study is examined to show the application of the mathematical programming formulation.

Original language	British English
Pages (from-to)	3284-3289
Number of pages	6
Journal	Energy Procedia
Volume	158
DOIs	https://doi.org/10.1016/j.egypro.2019.01.982
State	Published - 2019
Event	10th International Conference on Applied Energy, ICAE 2018 - Hong Kong, China Duration: 22 Aug 2018 → 25 Aug 2018

Keywords

L-shaped decomposition algorithm
Organic MSW management
Stochastic optimization
Supply chain

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.egypro.2019.01.982

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title = "A decomposition algorithm for organic solid waste supply chain optimization under uncertainty",

abstract = "Storage of municipality solid waste (MSW) in landfills is a common practice of the past. Negative impacts of landfills have motivated interest in the sustainable utilization of MSW. In this study, we cover the treatment of the organic MSW supply chain problem. The supply chain network is composed by several arcs connecting sources of organic MSW by treatment facilities, and markets imposing demand for power. A two-stage stochastic MILP model is formulated to examine the effects of the supply-demand, and power price uncertainties. The first stage decision variables involve technology and capacity selection. The second stage decision variables deal with transportation, and power production. The main contribution of the research study is the application of an L-shaped decomposition algorithm to solve a large scale organic MSW supply chain model under uncertainty. Another contribution is the application of a minmax regret risk model to analyze the financial risk in the organic MSW supply chain problem. A case study is examined to show the application of the mathematical programming formulation.",

keywords = "L-shaped decomposition algorithm, Organic MSW management, Stochastic optimization, Supply chain",

author = "Yousef Saif and Muhammed Rizwan and Ali Almansoori and Ali ElKamel",

note = "Publisher Copyright: {\textcopyright} 2019 The Authors. Published by Elsevier Ltd.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Peer-review under responsibility of the scientific committee of ICAE2018 The 10th International Conference on Applied Energy.; 10th International Conference on Applied Energy, ICAE 2018 ; Conference date: 22-08-2018 Through 25-08-2018",

year = "2019",

doi = "10.1016/j.egypro.2019.01.982",

language = "British English",

volume = "158",

pages = "3284--3289",

journal = "Energy Procedia",

issn = "1876-6102",

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}

TY - JOUR

T1 - A decomposition algorithm for organic solid waste supply chain optimization under uncertainty

AU - Saif, Yousef

AU - Rizwan, Muhammed

AU - Almansoori, Ali

AU - ElKamel, Ali

N1 - Publisher Copyright: © 2019 The Authors. Published by Elsevier Ltd.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Peer-review under responsibility of the scientific committee of ICAE2018 The 10th International Conference on Applied Energy.

PY - 2019

Y1 - 2019

N2 - Storage of municipality solid waste (MSW) in landfills is a common practice of the past. Negative impacts of landfills have motivated interest in the sustainable utilization of MSW. In this study, we cover the treatment of the organic MSW supply chain problem. The supply chain network is composed by several arcs connecting sources of organic MSW by treatment facilities, and markets imposing demand for power. A two-stage stochastic MILP model is formulated to examine the effects of the supply-demand, and power price uncertainties. The first stage decision variables involve technology and capacity selection. The second stage decision variables deal with transportation, and power production. The main contribution of the research study is the application of an L-shaped decomposition algorithm to solve a large scale organic MSW supply chain model under uncertainty. Another contribution is the application of a minmax regret risk model to analyze the financial risk in the organic MSW supply chain problem. A case study is examined to show the application of the mathematical programming formulation.

AB - Storage of municipality solid waste (MSW) in landfills is a common practice of the past. Negative impacts of landfills have motivated interest in the sustainable utilization of MSW. In this study, we cover the treatment of the organic MSW supply chain problem. The supply chain network is composed by several arcs connecting sources of organic MSW by treatment facilities, and markets imposing demand for power. A two-stage stochastic MILP model is formulated to examine the effects of the supply-demand, and power price uncertainties. The first stage decision variables involve technology and capacity selection. The second stage decision variables deal with transportation, and power production. The main contribution of the research study is the application of an L-shaped decomposition algorithm to solve a large scale organic MSW supply chain model under uncertainty. Another contribution is the application of a minmax regret risk model to analyze the financial risk in the organic MSW supply chain problem. A case study is examined to show the application of the mathematical programming formulation.

KW - L-shaped decomposition algorithm

KW - Organic MSW management

KW - Stochastic optimization

KW - Supply chain

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U2 - 10.1016/j.egypro.2019.01.982

DO - 10.1016/j.egypro.2019.01.982

M3 - Conference article

AN - SCOPUS:85063884775

SN - 1876-6102

VL - 158

SP - 3284

EP - 3289

JO - Energy Procedia

JF - Energy Procedia

T2 - 10th International Conference on Applied Energy, ICAE 2018

Y2 - 22 August 2018 through 25 August 2018

ER -

A decomposition algorithm for organic solid waste supply chain optimization under uncertainty

Abstract

Keywords

UN SDGs

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