FIXED ORDER BRANCH AND BOUND METHODS FOR MIXED-INTEGER PROGRAMMING.

The aim of this dissertation is to present an algorithm for mixed integer programs which when started with a good heuristic solution can find improved solutions and reduce the error estimate as quickly as possible. This is achieved by using two ideas: a fixed order branch-and-bound method with selective expansion of subproblems and the sieve strategy which uses stronger than optimal bounds. The fixed order branch-and-bound method with selective expansion of subproblems is effective in reducing the error estimate quickly whereas the sieve strategy is effective in reducing the error estimate as well as finding improved solutions quickly. Computational experience is reported