The simulation results obtained by our proposed GA were compared with those obtained by two other stochastic search methods, namely simulated annealing (SA) and Tabu search (TS), as well as a nonlinear integer programming-based method, branch-and-bound (BB).
This paper proposes the solution by DE of process engineering problems and compares its computational performance with an exact optimization method (Branch-and-Bound) and with a Genetic Algorithm.
In this paper, we use tabu search to solve this feature selection problem and compare it with classic algorithms, such as sequential methods, branch and bound method, etc., and most other suboptimal methods proposed recently, such as genetic algorithm and sequential forward (backward) floating search methods.
Even though global optimization techniques (e.g., exhaustive search-based solution methods, branch and bound method) can be adapted to find the optimal solution of problem (5), the complexity of these approaches grows exponentially with the size of the network.
Besides, an exact method, called branch-and-bound method via GAMS optimization software, is used to compare lower and upper bounds of Pareto fronts to optimize two single-objective problems separately.
If both conditions in line 16 and line 21 are not met, then the method branches out and prunes the current.
The method combines branch-and-bound search with a constrain-and-generate principle to minimize the surface of the conformation (objective shown to be similar with maximizing the number of H-H contacts).
To form the composite functions, they proposed some classical optimization methods such as cutting plane method and branch and bound algorithm.
Computational experiments indicate that among those methods, the branch and bound method is best suited to solve problems of realistic size.
The optimal IL solvents are identified using a deterministic optimization method with branch and bound algorithm.
Lesh et al. (2004) modified the approach by adding the pruning method with branch and bound to solve a small subset of this problem.
