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Operational Research Notes Mathematical Programming Notes

Transportation Problem Notes

Updated Transportation Problem Notes

Mathematical Programming Notes

Mathematical Programming

Approximately 42 pages

In depth, typed notes covering the Mathematical Programming (OR202.2) course at LSE (London School of Economics) which is part of the Operational Research Methods (OR202) course along with Operational Research Techniques (OR202.1). Covers the full content of the course including the following topics:

- Linear Programming
- Feasibility
- Optimality
- Minimisation and Maximisation Problems
- Formulation
- Non-negativities
- Sensitivities
- The Dual Program
- Transportation Problem

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The following is a more accessible plain text extract of the PDF sample above, taken from our Mathematical Programming Notes. Due to the challenges of extracting text from PDFs, it will have odd formatting:

Lecture 9: Transportation Problem Topics * Transport formulation * Redundant constraint * More graph theory * Feasibility * Optimality * Moving to another solution * Finding an initial solution * Steps of the transport algorithm * Example * Multiple optimal solutions * Degeneracy Reading Key Points * Formulating transportation problems * Dummy sources and destinations * Redundant constraints * Tree graphs * Vertex-arc incidence matrices * Feasibility of proposed solutions * Optimality checking * Calculating dual values * Non-basic variables * Optimality using cost matrix * Moving to another solution * North-west corner rule Transport Formulation * Transport Problem = Given m sources of a homogeneous commodity and n destinations for it with known quantities of supply and demand, given the cost of transport from each source to each destination, find the pattern of distribution from sources to destinations which will minimise total transport cost * The formulation assumes that the total available amount is equal to the total amount required * We can create a dummy source or destination if this is not the case ? This will have zero cost provided there is no penalty Example of a transportation formulation * Least-cost method * Interpretation of dual values of non-basic variables * Degeneracy Definitions * North-West Corner Rule = A simple method to obtain a first solution of a TP by selecting the cell in the north-west corner of the matrix, and assigning it the minimum of the amount required by destination 1 and the amount available at source 1 * Transport Problem = Given m sources of a homogeneous commodity and n destinations for it with known quantities of supply and demand, given the cost of transport from each source to each destination, find the pattern of distribution from sources to destinations which will minimise total transport cost * Tree = A graph with n vertices and n-1 arcs which is connected, so that ignoring the direction of the arcs, it is possible to go from every vertex to every other Formulae * * * Dual of the destination - Dual of the source = Cost of the route * Dual value = dual of the destination - dual of the source - cost of the route * Each column has two non-zero elements, a -1 and a +1 * In column , the -1 is in the row associated with source i * The +1 is in the row associated with destination j * This property is true for all transportation problems Redundant Constraint * The formulation has m+n equality constraints * Because total supply = Total demand * This means one of the equality constraints is redundant * If any one of the constraints were to be deleted from the formulation, then any feasible solution satisfying the remaining constraints would necessarily satisfy the deleted constraint * [?] there are only m+n-1 independent constraints More Graph Theory * Tree = A graph with n vertices and n-1 arcs which is connected, so that ignoring the direction of the arcs, it is possible to go from every vertex to every other Example of a tree graph * * A way of representing a directed graph is by a vertex-arc incidence matrix * The rows of the matrix correspond to the vertices * The columns of the matrix correspond to the arcs Example of a vertex-arc incidence matrix Course Notes Page 16

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