Using Column Generation To Solve A Coal Blending Problem

Daniel de Wolf (), Stéphane Auray and Yves Smeers
Additional contact information
Daniel de Wolf: TVES - Territoires, Villes, Environnement & Société - ULR 4477 - ULCO - Université du Littoral Côte d'Opale - Université de Lille, ULCO - Université du Littoral Côte d'Opale
Yves Smeers: CORE - Center of Operation Research and Econometrics [Louvain] - UCL - Université Catholique de Louvain = Catholic University of Louvain, UCLouvain

Post-Print from HAL

Abstract: In this paper, we formulate and solve a real life coal blending problem using a Column Generation Approach. The objective of the model is to prescribe optimal mixes of coal to produce coke. The problem is formulated as a mixed integer program. It involves various types of constraints arising from technical considerations of the blending process. The model also incorporates nonlinear constraints. It results in a large-scale problem that cannot be solved by classical operations research methods. Defining three heuristic methods based on column generation techniques, this paper proposes reasonable solutions for the industry.

Keywords: Column generation; coal blending (search for similar items in EconPapers)
Date: 2015-01
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-02396784
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in RAIRO - Operations Research, 2015, 49 (1), pp.15-37. ⟨10.1051/ro/2014033⟩

Downloads: (external link)
https://shs.hal.science/halshs-02396784/document (application/pdf)

Related works:
Working Paper: Using column generation to solve a coal blending problem (2015)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-02396784

DOI: 10.1051/ro/2014033

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().