Two new coronavirus-based metaheuristic algorithm ... objective function can be considered a trade-off between the makespan and the total completion time. Finally, we compared the performances of the ...

This paper presents a two-stage sparse multi-objective ... values obtained by TS-MOEA and other MOEAs. The numbers in bold are the best results achieved by algorithms and bold numbers in other tables ...

It is particularly useful for combinatorial optimization problems defined by complex objective functions ... algorithm requires that we track states (current, previous, best), which means we need to ...

Integer programming is a type of optimization problem where you need to find the best ... the two solution are equal and solving the LP relaxation suffices The objective function value of LP ...

Despite numerous research efforts to create novel optimization algorithms for solving multi-objective optimization problems, the trade-off between solution speed and the number of function ... the ...

The assumption of linear regression is that the objective function ... algorithms can find solutions to supervised learning problems that ask for a choice (or determination of probability) between ...

It provides a very imperative interface to fully support Python language ... In this objective function we will consider both ridge and lasso regularization methods and compare their values and find ...

Have you ever wondered how we humans evolved so much? – because we learn from our mistakes and try to continuously improve ourselves on the basis of those mistakes now the same case is with machines, ...