A New Hybrid for Software Cost Estimation Using Particle Swarm Optimization and Differential Evolution Algorithms
نویسندگان
چکیده
Software Cost Estimation (SCE) is considered one of the most important sections in software engineering that results in capabilities and well-deserved influence on the processes of cost and effort. Two factors of cost and effort in software projects determine the success and failure of projects. The project that will be completed in a certain time and manpower is a successful one and will have good profit to project managers. In most of the SCE techniques, algorithmic models such as COCOMO algorithm models have been used. COCOMO model is not capable of estimating the close approximations to the actual cost, because it runs in the form of linear. So, the models should be adapted that simultaneously with the number of Lines of Code (LOC) has the ability to estimate in a fair and accurate fashion for effort factors. Metaheuristic algorithms can be a good model for SCE due to the ability of local and global search. In this paper, we have used the hybrid of Particle Swarm Optimization (PSO) and Differential Evolution (DE) for the SCE. Test results on NASA60 software dataset show that the rate of Mean Magnitude of Relative Error (MMRE) error on hybrid model, in comparison with COCOMO model is reduced to about 9.55%.
منابع مشابه
Software Cost Estimation by a New Hybrid Model of Particle Swarm Optimization and K-Nearest Neighbor Algorithms
A successful software should be finalized with determined and predetermined cost and time. Software is a production which its approximate cost is expert workforce and professionals. The most important and approximate software cost estimation (SCE) is related to the trained workforce. Creative nature of software projects and its abstract nature make extremely cost and time of projects difficult ...
متن کاملOptimization of grid independent diesel-based hybrid system for power generation using improved particle swarm optimization algorithm
The power supply of remote sites and applications at minimal cost and with low emissions is an important issue when discussing future energy concepts. This paper presents modeling and optimization of a photovoltaic (PV)/wind/diesel system with batteries storage for electrification to an off-grid remote area located in Rafsanjan, Iran. For this location, different hybrid systems are studied and ...
متن کاملEconomic Dispatch of Thermal Units with Valve-point Effect using Vector Coevolving Particle Swarm Optimization Algorithm
Abstract: This paper is intended to reduce the cost of producing fuel from thermal power plants using the problem of economic distribution. This means that in order to determine the share of each unit, considering the amount of consumption and restrictions, including the ones that can be applied to the rate of increase, the prohibited operating areas and the barrier of the vapor barrier, the pr...
متن کاملA New Optimized Hybrid Model Based On COCOMO to Increase the Accuracy of Software Cost Estimation
The literature review shows software development projects often neither meet time deadlines, nor run within the allocated budgets. One common reason can be the inaccurate cost estimation process, although several approaches have been proposed in this field. Recent research studies suggest that in order to increase the accuracy of this process, estimation models have to be revised. The Construct...
متن کاملControl of nonlinear systems using a hybrid APSO-BFO algorithm: An optimum design of PID controller
This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...
متن کامل