Hi!

There is no difference between them. In general, the objective function is associated with the problem. In the context of an evolutionary algorithm, the "quality" or "fitness" of an individual is measured using the objective function. There are no two different functions, it is just a matter on how things are explained

Regards

David

Hi!

There is no difference between them. In general, the objective function is associated with the problem. In the context of an evolutionary algorithm, the "quality" or "fitness" of an individual is measured using the objective function. There are no two different functions, it is just a matter on how things are explained

Regards

David

I agree with David A Pelta. There is no difference. The correctness / accuracy of any optimization method depends on its Objective / fitness function being used in the algorithn

Hi,

Fitness function (real & positive value f >> 0) is a numerical representation of objective function, which knows as the performance. Fitness function  is normally used to transform the objective function value into a a non-negative number, and It may have different values in comparison with the original objective function defined for an optimization problem.

Ref.

A. Chipperfield, P. Fleming, H. Pohlheim, C. Fonseca, Genetic Algorithm TOOLBOX For Use with MATLAB, Automatic Control and System Engineering, University of Sheffield.

im still confuse about analogy of Objective function on PSO;

ABC                       =         Analogy                  = PSO

Food Source        = Solution                         = Best Particle position

Quaility of Nectar = Objective Function       = ??????????????????????

Onlooker bee       = Exploitation of Search  = Slow Velocity, around Pbest

Scout bee             = Exploration of Search   = High Velocity, around Gbest

can anyone explain me the ?????????

thanks

Fitness function  is an alternate internal numerical representation of the objective function, more appropriate for the correct working of the optimization algorithm, but by minimizing the fitness function, the objective function is minimized (or maximized) implicitly. So we can say that the two representations are equivalent!

Hi,

When the optimization problem is unconstrained, there is no difference.

When the optimization problem is constrained, and you are applying an evolutionary algorithm, you have a couple of design choices. One is to incorporate the constraints into the genetic encoding and the crossover and mutation operators, so that all members of the population are feasible. The other is to allow infeasible solutions to be generated and to penalize them. In the latter case, the fitness function is a blend of the original objective function and the penalty for in-feasibility.

Paul Rubin

working with optimization algorithms some terms strongly related but there is slight difference between them

The Object function it is the actual objective of the problem such as in generation we need to minimize the generation cost so the objective function is the generation cost

The fitness function it measures the fitness of the solution to the objective function. in some applications fitness function is same as objective function and other not . such as in cost minimization there are some constrains for example minimize the cost but satisfy the load and work within limits. in such constrained problem fitness function contains two part the object function and penalty function .

Penalty function is the function which added in fitness function when constraints are violated to make the solutions feasible and discard the unfeasible solutions

Scaling function scales the fitness function to be suitable for your algorithm. for example if the fitness function is varying from -1 to 1 and your algorithm needs the fitness to be positive we can make scaling to be in range (0 to 2) by adding 1 to our original function. OR from (0 5) by multiply by 5 and add 5

some problem the object function is not constrained and suitable for the algorithm so that all detailed definitions are not important

i hope that is clear and helpful