This paper addresses the problem of simultaneous localization and mapping (SLAM) by a mobile robot. The SLAM problem is defined as a global optimization problem in which the objective is to search the space of possible robot maps. A genetic algorithm is described for solving this problem, in which a population of candidate solutions is progressively refined in order to find a globally optimal s...

The human has always been to up to the best in everything, And this perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables to find the best acceptable answer to the limitations in a problem, so that the objective function is a minimum or a maximum. Metaheuristic algorithms are one of inaccurate optimization methods that inspired by ...

The vehicle routing problem with simultaneous pickup and delivery (VRPSPD) is a well-known combinatorial optimization problem which addresses provided service to a set of customers using a homogeneous fleet of capacitated vehicles. The objective is to minimize the distance traveled. The VRPSPD is an NP-hard combinatorial optimization problem. Therefore, practical large-scale instances of VR...

The vehicle routing problem with simultaneous pickup and delivery (VRPSPD) is a well-known combinatorial optimization problem which addresses provided service to a set of customers using a homogeneous fleet of capacitated vehicles. The objective is to minimize the distance traveled. The VRPSPD is an NP-hard combinatorial optimization problem. Therefore, practical large-scale instances of VR...

Studying the theoretical properties of optimization algorithms such as genetic and evolutionary strategies allows us to determine when they are suitable for solving a particular type problem. Such study consists three main steps. The first step is considering Stochastic Global Optimization Algorithms (SGoals ), i.e., iterative algorithm that applies stochastic operations set candidate solutions...

In this paper, an innovative Genetic Algorithms (GA)-based inexact non-linear programming (GAINLP) problem solving approach has been proposed for solving non-linear programming optimization problems with inexact information (inexact non-linear operation programming). GAINLP was developed based on a GA-based inexact quadratic solving method. The Genetic Algorithm Solver of the Global Optimizatio...

this paper presents a new nonlinear mathematical model to solve a cell formation problem which assumes that processing time and inter-arrival time of parts are random variables. in this research, cells are defined as a queue system which will be optimized via queuing theory. in this queue system, each machine is assumed as a server and each part as a customer. the grouping of machines and parts...

In the past, several force structure analyses have been conducted for the Canadian Armed Forces using moderate fidelity (e.g., Tyche) and low-fidelity (e.g. Stochastic Fleet Estimation or SaFE) simulation models within optimization frameworks. Monte Carlo discrete event simulations like Tyche are computationally expensive and can only be used in optimizations that require few force structure ev...