A Bee Colony Optimization Algorithm Approach for Software Cost Estimation
TL;DR: Improve the accuracy of the cost estimation by using Bee Colony Optimization algorithm by reducing the mean absolute relative error to 0.1619.
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Abstract: In this paper, we intend to improve the accuracy of the cost estimation by using Bee Colony Optimization algorithm. It should be mentioned that the proposed method is compared with the intermediate COCOMO. The results indicate that the proposed method have reduced the mean absolute relative error to 0.1619.
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Citations
Software engineering economics
Barry Boehm
- 01 Jan 1981
TL;DR: In this article, the authors provide an overview of economic analysis techniques and their applicability to software engineering and management, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.
380
A new approach by using Tabu search and genetic algorithms in Software Cost estimation
Farhad Soleimanian Gharehchopogh,Raheleh Rezaii,Bahman Arasteh +2 more
- 01 Oct 2015
TL;DR: In this article, the authors used hybrid of genetic algorithm and Tabu search algorithm that are types of metaheuristic algorithms could play a significant role in engineering optimization issues in software cost estimation.
References
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Software Engineering Economics
Barry Boehm
- 01 Jan 1981
TL;DR: In this article, the authors provide an overview of economic analysis techniques and their applicability to software engineering and management, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.
6K
Software engineering economics
Barry Boehm
- 04 Oct 1993
TL;DR: In this paper, the authors provide an overview of economic analysis techniques and their applicability to software engineering and management, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.
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A General Empirical Solution to the Macro Software Sizing and Estimating Problem
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Computing with bees: attacking complex transportation engineering problems
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TL;DR: The Bee System represents the new, successful application of emergent techniques based on natural metaphors, such as simulated annealing, genetic algorithms, and neural networks, to the complex engineering and management problems.
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