Semi-deterministic versus genetic algorithms for global optimisation of multichannel optical filters

Abstract

Abstract:A new global optimization algorithm is presented and applied to the design of high-channel-count multichannel filters based on sampled Fiber Bragg Gratings. We focus on the realization of particular designs corresponding to multichannel filters that consist of 16 and 38 totally reflective identical channels spaced 100 GHz. The results are compared with those obtained by a hybrid genetic algorithm and by the classical sinc method.

A Variance-Expected Compliance Model for Structural Optimization

“…In order to solve (D V ar ; IP; α; β), which seems to be a non-convex problem (the cost function associated to the problem appears to have various local minima, see Figure 2), we use a particular global optimization algorithm based on the steepest descent algorithm, where the initial condition is generated using the secant method [25]. A complete description and validation of this algorithm can be found in the following literature [20,18,13,22,21,16,17]. The obtained solutions are denoted by λ (α,β) .…”

Optimization strategies in credit portfolio management

“…In other words, the zone near this element will be better explored. In other cases, the secant method used in Step 2.2 allows to redistribute the initial population far from the current solution (See [7,10,11] for more details).…”

“…It has been applied and compared with a classical genetic algorithm on various benchmark test cases [7] and industrial applications [10,11,12,13].…”

A low-complexity global optimization algorithm for temperature and pollution control in flames with complex chemistry

“…We would like therefore to use a low complexity global minimization algorithm previously applied with success to various nonlinear industrial optimization problems [13,14,16].…”

“…This algorithm allows to escape from local minima at a lower cost than genetic algorithms [12,13,14].…”