An Algoritm for the Alocation Optimization of Trading Executions

In this paper, I wish to propose the Integer Allocation employing Tabu Search in conjunction with Simulated Annealing Heuristics for optimizing the distribution of trading executions in investors’ accounts. There is no polynomial algorithm discovered for Integer Linear Programming (a problem which is NP-complete). Generally, the practical experience shows that large-scale integer linear programs seem as yet practically unsolvable or extremely time-consuming. The algorithm described herein proposes an alternative approach to the problem. The algorithm consists of three steps: allocate the total executed quantity proportionally on the accounts, based on the allocation instructions (pro-rata basis); construct an initial solution, distributing the executed prices; improve the solution iteratively, employing Tabu Search in conjunction with Simulated Annealing heuristics.