Calls for papers

 

International Journal of Mathematics in Operational Research

 

Special Issue on: "Solving Large-scale Linear Programs"

Guest Editor: Dr. Moustapha Diaby, University of Connecticut, USA

With the ever-increasing degree of globalisation of business enterprises, the field of Operations Research (OR) has been continuously presented with new challenges over the past few decades. The increasing scarcity of resources combined with market requirements for high-quality customisation and, at the same time, low-costs are making the need to optimise products and processes by looking at the entire supply chain increasingly vital.

One consequence of this is that problems that are nowadays routinely faced by OR practitioners have scales that would be unimaginable only a couple of decades ago. In addition, the realisation of the full potentials of many of the recent modelling developments (e.g. related to "hard" combinatorial problems, or stochastic optimisation problems) has generally called for the ability to solve large-scale linear programming (LP) problems efficiently.

Great strides at solving very-large-scale LP's have been made over the past two decades. These strides are attributable mostly to increases in computing power and new implementation approaches, along with new theoretical developments. However, fundamental issues having to do with memory limitations, numerical stability, degeneracy, and cycling, for example, have continued to pose great challenges in practice.

The purpose of this special issue is to take stock of the state-of-the-art of solution approaches for very-large-scale linear programming problems, and to help bring greater focus from the research community on the current issues and challenges in solving these problems.

Subject Coverage
Topics of interest for this special issue focus on solving large-scale linear programs and include, but are not limited to:

• state-of-the-art reviews
• new theoretical developments
• computational studies
• column-generation approaches
• decomposition (resource-directed price directed) approaches
• distributed computing
• factorisation/re-factorszation approaches
• interior-point methods
• LP modelling and solution approaches for stochastic optimisation
• modelling approaches for "hard" combinatorial optimisation problems
• novel data structures for implementation
• parallel processing approaches
• primal-dual methods

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere

All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page

Important Dates

Submissions will be accepted until: 31 May, 2010

Final drafts of accepted papers must be received by: 27 August, 2010