| EPSRC Reference: |
EP/C500148/1 |
| Title: |
An investigation into zero-one Stochastic mixed integer programming solution method |
| Principal Investigator: |
Poojari, Dr C |
| Other Investigators: |
|
| Researcher Co-Investigators: |
|
| Project Partners: |
|
| Department: |
Mathematical Sciences |
| Organisation: |
Brunel University London |
| Scheme: |
Mathematics Small Grant PreFEC |
| Starts: |
26 May 2005 |
Ends: |
25 August 2005 |
Value (£): |
9,850
|
| EPSRC Research Topic Classifications: |
| Mathematical Aspects of OR |
|
|
| EPSRC Industrial Sector Classifications: |
|
| Related Grants: |
|
| Panel History: |
|
|
Summary on Grant Application Form |
|
Stochastic Zero-one mixed integer programming (SZMIP) models are being increasingly applied in the modelling and analysis of financial planning and supply chain management problems. SZMIP models explicitly consider discrete decisions and model uncertainty and thus provide hedged decisions that perform well under several scenarios. The NP-Hard nature of the underlying model (due to the discrete variables) together with the curse of dimensionality (due to the underlying random variables) make these models computationally challenging research topics. Useful mathematical structural properties such as continuity, convexity and duality are absent in such classes of models. . We propose to develop an automatic procedure to identify, classify and analyse the generic model structures (such as knapsack, set covering, set partitioning and fixed charge) using graph representations and exploit them by graph theoretical algorithms. These procedures will be investigated within our existing decomposition and branchand-cut based computational framework. The insight gained during this research will be used to (i) reduce the dimension of the problem by removing redundant variables and constraints, fixing the variables and bounding the constraints (pre-processing), (ii) generate strong cuts for the specific substructures that would approximate the convex hull of the solution space (cutting planes), (iii) identify good feasible solutions (primal heuristics).
|
|
Key Findings |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Potential use in non-academic contexts |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
|
Impacts |
|
| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
|
| Date Materialised |
|
|
|
|
Sectors submitted by the Researcher |
|
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
| Project URL: |
|
| Further Information: |
|
| Organisation Website: |
http://www.brunel.ac.uk |