Software project scheduling method based on heuristic discrete artificial bee colony algorithm
An artificial bee colony algorithm and software project technology, applied in the field of software project scheduling based on heuristic discrete artificial bee colony algorithm, can solve problems such as easy to fall into local optimum, slow convergence speed, low solution accuracy, etc., to improve local search Excellent ability, increased diversity, and excellent performance
Pending Publication Date: 2022-04-08
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology
The basic artificial bee colony algorithm search is blind, the convergence speed is slow, and it is easy to fall into local optimum, and the solution accuracy is low. In summary, a software project with higher convergence efficiency and strong ability to jump out of local optimum is proposed Scheduling method is extremely necessary
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[0105] Below in conjunction with accompanying drawing and specific embodiment, further illustrate the present invention, should be understood that these examples are only for illustrating the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various aspects of the present invention All modifications of the valence form fall within the scope defined by the appended claims of the present application.
[0106] In an actual project, there are 10 employees and 15 tasks (that is, M=10, N=15), and there are a total of 6 skill requirements (set as 1, 2, 3, 4, 5, 6, and the skill difficulty is 0.4 , 0.4, 0.5, 0.6, 0.7, 0.5), where skill 6 is a new skill. task priority chart figure 2 shown. Each task T j workload required And the set of skill requirements req j As shown in Table 1. Each employee i The maximum allowable amount of work devoted to the entire project ...
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The invention discloses a software project scheduling method based on a heuristic discrete artificial bee colony algorithm, which comprises the following steps of: (1) reading project information including attributes of tasks and employees; (2) designing a new skill learning mechanism; (3) initializing algorithm parameters; (4) generating an initial nectar source population, and calculating a target value; (5) the leading bees globally search the nectar source through a multivariate learning strategy; (6) carrying out local search on the nectar source by the following bees through a variation mechanism based on heuristic information; (7) the reconnaissance bees abandon useless nectar sources, and new nectar sources are randomly generated again to replace the old nectar sources; and (8) judging whether the number of iterations reaches the maximum value or not, if so, terminating the iteration, and outputting an individual with an optimal target value, the individual being the scheduling result of the input degree of each employee in each task in the project. The method has the advantages of high search capability and high efficiency of the generated scheduling scheme.
Description
technical field [0001] The invention belongs to the field of project management, and in particular relates to a software project scheduling method based on a heuristic discrete artificial bee colony algorithm. Background technique [0002] In recent years, the software industry has developed into an important industry of the national economy. The state has issued relevant documents such as "Several Policies for Promoting the High-quality Development of the Integrated Circuit Industry and Software Industry in the New Era" to further optimize the development environment of the software industry, deepen international cooperation in the industry, and improve industrial innovation capabilities and development quality. Software Project Scheduling (SPSP) is an important link in software development, which directly affects the economic benefits and market competitiveness of software companies. SPSP refers to finding a reasonable arrangement of human resources and tasks, minimizing ...
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Login to View More IPC IPC(8): G06Q10/04G06Q10/06G06N3/00G06N3/12
Inventor 申晓宁姚铖滨徐继勇葛忠佩许笛
Owner NANJING UNIV OF INFORMATION SCI & TECH