Scenario analysis often is used to determine bottlenecks in multimodal transportation and logistics chains. Bottleneck-analysis itself is a process related approach to identify shortages in multimodal transportation and logistics supply chains, and concerned with analysis of resource planes, optimization of multimodal transportation chains, consideration of timeliness and concurrency using reso...

This study introduces an effective population-based optimization algorithm, namely the Golden Search Optimization Algorithm (GSO), for numerical function optimization. The new algorithm has a simple but strategy solving complex problems. GSO starts with random possible solutions called objects, which interact each other based on mathematical model to reach global optimum. To provide fine balanc...

Multiobjective selection operators are a popular and straightforward tool for preserving diversity in evolutionary optimization algorithms. One application area where diversity is essential is multimodal optimization with its goal of finding a diverse set of either globally or locally optimal solutions of a single-objective problem. We therefore investigate multiobjective selection methods that...

Optimization algorithms play a critical role in electromagnetic device designs due to the ever-increasing technological and economical competition. Although evolutionary algorithm-based methods have successfully been applied different design problems, these exhibit deficiencies when solving complex problems with multimodal discontinuous objective functions, which is quite common optimization de...

In this paper we describe the design and implementation of an adaptive multimodal fission component integrated in the multimodal GUIDE framework. This component is able to adapt any TV based application’s UI to a specific user’s characteristics making possible for elderly and impaired users to interact by offering several output modalities that tries to overcome his difficulties of interaction.

The paper illustrates the application of a combined adaptive particle swarm optimization (A-PSO) algorithm and the finite strip method (FSM) to the lay-up optimization of symmetrically fiber-metal laminated (FML) composite shallow shell panels for maximizing the fundamental frequency. To improve the speed of the optimization process, adaptive inertia weight was used in the particle swarm optimiz...

Multimodal sentiment analysis has increasingly attracted attention since with the arrival of complementary data streams, it great potential to improve and go beyond unimodal analysis. In this article, we present an efficient separable multimodal learning method deal tasks modality missing issue. method, tensor is utilized guide evolution each separated representation. To save computational expe...

In medical imaging, the use of different imaging modalities has significantly enhanced diagnostic information available to physicians. Each type modality exhibits unique about subject being imaged. many cases, physicians are interested in multimodal same organ, which is complementary nature and its fusion often required. A lot methods proposed address image problem. However, main downside all s...

A method of self-adaptive mutation, crossover and selection was implemented and applied in four genetic algorithms. So developed self-adapting algorithms were then compared, with respect to convergence, with a traditional genetic one, which contained constant rates of mutation and crossover. The experiments were conducted on six benchmark functions including two unimodal functions, three multim...