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Published:
Apr 6, 2022Article Details
Tanzania Journal of Engineering and Technology (Tanz. J. Engrg. Technol.) publications are written as a basis for academic discussions. Whereas effort is made by the Editorial Board to screen out inaccurate or misleading statements, data or opinions, Tanz. J. Engrg. Technol. wishes to make it clear that the contents of the articles are the sole responsibility of the authors. Accordingly, the Editorial Board and editors, publisher, College of Engineering and Technology and the University of Dar es Salaam accept no responsibility or liability whatsoever for the opinions, inaccurate or misleading data or statement and views expressed by the authors.
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Main Article Content
Complete Neighbourhood Search Heuristic Algorithm for Portfolio Optimization
Abstract
In portfolio optimization, the fundamental goal of an investor is to optimally allocate investments between different assets. Mean-variance optimization methods make unrealistic assumptions to solve the problem of optimal allocation. On the other hand, when realistic constraints like holding size and cardinality are introduced it leads to optimal asset allocation which differ from the mean variance optimization. The resulting optimization problem become quite complex as it exhibits multiple local extrema and discontinuities. Heuristic algorithms work well for the complex problem. Therefore, a heuristic algorithm is developed which is based on hill climbing complete (HC-C). It is utilized to solve the extended portfolio optimization problem. In order to validate its performance, the proposed HC-C is tested with standard portfolio optimization problem. Experimental results are benchmarked with the quadratic programming method and threshold accepting (TA) algorithm.
