The Generalized Generation Gap (G3) algorithm is one of the most efficient and effective state-of-the-art realcoded genetic algorithms (RCGAs) for unconstrained global optimization. However, its performance on multimodal optimization problems is known to be poor compared to unimodal optimization problems. The G3 algorithm currently relies on crossover operations only. The objective of this pape...

In this paper, we study the optimization of a neural network used for controlling a Monte-Carlo Tree Search / Upper Confidence Trees (MCTS/UCT) algorithm. The main results are: (i) the specification of a new multimodal benchmark function; this function has been defined in particular in agreement with [1] which has pointed out that most multimodal functions are not satisfactory for some real-wor...

Graph-based Simultaneous Localization and Mapping (SLAM) has experienced a recent surge towards robust methods. These methods take the combinatorial aspect of data association into account by allowing decisions of the graph topology to be made during optimization. In this paper, the Generalized Graph SLAM framework for SLAM under ambiguous data association is presented, and a formal description...

Functional brain imaging is a source of spatio-temporal data mining problems. A new framework hybridizing multi-objective and multimodal optimization is proposed to formalize these data mining problems, and addressed through Evolutionary Computation (EC). The merits of EC for spatio-temporal data mining are demonstrated as the approach facilitates the modelling of the experts’ requirements, and...

Multimodal optimization is used to find multiple global & local optima which is very useful in many real world optimization problems. But often evolutionary algorithms fail to locate multiple optima as required by the system. Also they fail to store those optima by themselves. So we have to use other selection scheme that can detect & store multiple optima along with evolutionary algorithms. He...

Seeker optimization algorithm (SOA) is a novel search algorithm based on simulating the act of human searching, which has been shown to be a promising candidate among search algorithms for unconstrained function optimization. In this article we propose a modified seeker optimization algorithm. In order to enhance the performance of SOA, our proposed approach uses two search equations for produc...

background many multimodal analgesia techniques have been tried to provide adequate analgesia for midline incisions extending above and below the umbilicus aiming at limiting the perioperative use of morphine thus limiting side effects. ultrasound (us) guidance made the anesthesiologist reconsider old techniques for wider clinical use. the rectus sheath block (rsb) is a useful technique under-u...

This work investigates one immune optimization approach for dynamic constrained multi-objective multimodal optimization in terms of biological immune inspirations and the concept of constraint dominance. Such approach includes mainly three functional modules, environmental detection, population initialization and immune evolution. The first, inspired by the function of immune surveillance, is d...