In this paper, we study the sequential convex programming method with monotone line search (SCP$_{ls}$) in [Z. Lu, Sequential Convex Programming Methods for a Class of Structured Nonlinear Programm...

We investigate the recent Constrained Line Search algorithm for discriminative training of HMMs and propose an alternative formula for variance update. We compare the method to standard techniques on a phone recognition task.

This study focusses on a two objective type-2 simple assembly line balancing problem. Its primary is minimizing the cycle time, or equivalently, maximizing production rate of line. Minimization workload imbalance among workstations considered as secondary objective. Since problem known to be intractable, reactive tabu search algorithm proposed for solution. Although well-known meta-heuristic pr...

The gradient method is a very efficient iterative technique for solving unconstrained optimization problems. Motivated by recent modifications of some variants the SM method, this study proposed two methods that are globally convergent as well computationally efficient. Each under influence backtracking line search. Results obtained from numerical implementation these and performance profiling ...

It is often useful to know, in advance, how much effort will be required to solve a search problem. Current techniques for estimating the number of nodes that a bounded depth-first search will expand require copious amounts of off-line training and only make predictions in domains with integer-valued heuristic estimates. We present a new technique for estimating the number of nodes that a bound...