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IMPROVED EVOLUTIONARY ALGORITHM DESIGN FOR THE PROJECT SCHEDULING PROBLEM BASED ON RUNTIME ANALYSIS
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IMPROVED EVOLUTIONARY ALGORITHM DESIGN FOR THE PROJECT SCHEDULING PROBLEM BASED ON RUNTIME ANALYSIS

Category : Software Engneering


Sub Category : DOTNET


Project Code : ITDSW05


Project Abstract

IMPROVED EVOLUTIONARY ALGORITHM DESIGN FOR THE PROJECT SCHEDULING PROBLEM BASED ON RUNTIME ANALYSIS

 

ABSTRACT

Several variants of evolutionary algorithms (EAs) have been applied to solve the project scheduling problem (PSP), yet their performance highly depends on design choices for the EA. It is still unclear how and why different EAs perform differently. We present the first runtime analysis for the PSP, gaining insights into the performance of EAs on the PSP in general, and on specific instance classes that are easy or hard. Our theoretical analysis has practical implications—based on it, we derive an improved EA design. This includes normalizing employee’s dedication for different tasks to ensure they are not working overtime; a fitness function that requires fewer pre-defined parameters and provides a clear gradient towards feasible solutions; and an improved representation and mutation operator. Both our theoretical and empirical results show that our design is very effective. Combining the use of normalization to a population gave the best results in our experiments, and normalization was a key component for the practical effectiveness of the new design. Not only does our paper offer a new and effective algorithm for the PSP, it also provides a rigorous theoretical analysis to explain the efficiency of the algorithm, especially for increasingly large projects.

EXISTING SYSTEM

PROPOSED SYSTEM

E    EXISTING CONCEPT:-

In the previous design the PSP is particularly challenging when the project is large.

The space of possible allocations of employees to tasks is enormous, and providing an optimal allocation of employees to tasks becomes a very difficult task.

When allocating employees to tasks, employees can divide their attention among several tasks at the same time in the PSP.

 

PROPOSED CONCEPT:-

The new design includes normalization of dedication values, a tailored mutation operator, and fitness functions with a strong gradient towards feasible solutions.

Normalization removes the problem of overwork and allows an EA to focus on the solution quality.

 It facilitates finding the right balance between dedication values for different tasks and allows employees to adapt their workload whenever other tasks are started or finished.

E   EXISTING TECHNIQUE:-

Software project scheduling

PROPOSED TECHNIQUE:-

Software project management, COCOMO Model     

      TECHNIQUE DEFINITION:-

The PSP is particularly challenging when the project is large. The space of possible allocations of employees to tasks is enormous, and providing an optimal allocation of employees to tasks becomes a very difficult task

TECHNIQUE DEFINITION:-

It is a particularly demanding task and, being a project planning task, is vital to many software engineering activities. Its process involves several duties identify project activities; identify activity dependencies; estimate Resources for activities; allocate people to activities; and create project charts.

      DRAWBACKS:-

It is traditionally one of the major problems faced by software project managers

 

ADVANTAGES:-

Helps software manager in producing schedules that meet all constraints

Provide a very useful insight into how to optimize objectives such as cost and completion time


 
 
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