Summary
Process systems engineering is one of the many areas in which mixed integer optimisation formulations have been successfully applied. The nature of the problems requires specialised solution strategies and computer packages or callable libraries able to be extended and modified in order to accommodate new solution techniques. Object-oriented programming languages have been identified to offer these features. Process system applications are usually of large scale, and require modelling and solution techniques with high level of customisation. ooMILP is a library of C++ callable procedures for the definition, manipulation and solution of large, sparse mixed integer linear programming (MILP) problems without the disadvantages of many existing modelling languages. We first present a general approach to the packaging of numerical solvers as software components, derived from material developed for the CAPE-OPEN project. The presentation is in the context of construction and solution of Mixed Integer Linear Programming (MILP) problems. We then demonstrate how this package, based on the use of CORBA interfaces for synchronous execution within a single process, can be adapted with a minimum of problem-specific changes to provide a distributed solution.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cordier, C, H. Marchand, R. Laundry and L.A. Wolsey, “bc-opt: a Branch-and-Cut Code for Mixed Integer Programs”, Mathematical Programming, 86, 335–353, 1999.
Dimitriadis, A.D., “Algorithms for the Solution of Large-Scale Scheduling Problems”, PhD thesis, Imperial College, University of London, 2000.
Fisher, M.L., “The Lagrangean Relaxation Method for Solving Integer Programming Problems”, Management Science, 27, 1–18, 1981.
Geoffrion, A.M., “Generalized Benders Decomposition”, Journal of Optimization Theory and Applications, 4, 237–260, 1972.
Geoffrion, A.M., “Lagrangean Relaxation for Integer Programming”, Mathematical Programming Study 2, 2, 82–114, 1974.
Global CAPE-OPEN, “Mixed Integer Linear/Nonlinear Programming Interface Specifications”, http://www.co-lan.org, 2002.
Junger, M. and S. Thienel, “Introduction to ABACUS-a Branch-and-Cut System”, Operation Research Letters, 22(2–3), 83–95, 1998.
Message Passing Interface Forum, “MPI: A Message-Passing Interface standard”, International Journal of Supercomputer Applications, 8(3/4), 165–414, 1994.
Nemhauser, G.L., M.W.P. Savelsbergh and G.C. Sigismondi, “MINTO, a Mixed INTeger Optimizer”, Operation Research Letters, 15(1), 47–58, 1994.
Reeves, C.R., Modern Heuristic Techniques for Combinatorial Problems, Black-well Scientific Publications, London, 1993.
Tsiakis, P., B.R. Keeping and C.C. Pantelides, “ooMILP: A C++ Callable Object-Orientated Library for the Definition and Solution of Large, Sparse Mixed Integer Linear Programming (MILP) Problems”, Research Report, Centre for Process Systems Engineering, Imperial College of Science Technology and Medicine, London, 1999.
Tsiakis, P., A.D. Dimitriadis, N. Shah, C.C. Pantelides, “Solution of Nearly Decomposable MILP [ND-MILP] Problems”, AIChE Annual Meeting, Los Angeles, USA, 2000.
Tsiakis, P., N. Shah and C.C. Pantelides, “Design of Multi-Echelon Supply Chain Networks under Demand Uncertainty”, Industrial Engineering and Chemistry Research, 44(16), 3585–3604, 2001.
VanRoy, T.J., “A Cross Decomposition Algorithm for Capacitated Facility Location”, Operations Research, 34, 145–263, 1986.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer Science+Business Media, Inc.
About this chapter
Cite this chapter
Tsiakis, P., Keeping, B. (2006). ooMILP — A C++ Callable Object-oriented Library and the Implementation of its Parallel Version using CORBA. In: Liberti, L., Maculan, N. (eds) Global Optimization. Nonconvex Optimization and Its Applications, vol 84. Springer, Boston, MA. https://doi.org/10.1007/0-387-30528-9_12
Download citation
DOI: https://doi.org/10.1007/0-387-30528-9_12
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-28260-2
Online ISBN: 978-0-387-30528-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)