This paper introduces a new human-based metaheuristic algorithm called Sewing Training-Based Optimization (STBO), which has applications in handling optimization tasks. The fundamental inspiration of ...

In the realm of science, problems that have multiple feasible solutions are referred to as optimization problems. Therefore, finding the best feasible solution among all the available solutions for a ...

This chapter explores fundamental optimization concepts, emphasizing metaheuristic optimization techniques. It compares traditional and metaheuristic methods, highlighting their differences and ...

Abstract: By analyzing the similarity of a self-organizing system and an optimization process, we highlight that optimization can be considered as self-organization. We analyze the characteristics of ...

If you are working on a complex optimization problem, such as finding the best route for a delivery truck, you might need to use an algorithm that can find a good solution in a reasonable time. But ...

Ant Colony Optimization (ACO) is a metaheuristic inspired by real-world ant behavior, where ants communicate via pheromone trails to find optimal paths. Introduced by Marco Dorigo in the 1990s, ACO ...

En casa le llamamos Zelda. Ahora que sale a la calle lleva este nombre oficial: A Tutorial on the Design, Experimentation and Application of Metaheuristic Algorithms to Real-World Optimization ...

Genetic Algorithms (GA) are a powerful class of optimization algorithms inspired by the principles of natural selection and genetics. Developed by John Holland in the 1960s and 1970s, GAs are used to ...

ABSTRACT: This paper presents a multi-objective production planning model for a factory operating under a multi-product, and multi-period environment using the lexicographic (pre-emptive) procedure.