J. Kwiecień

Cockroach Swarm Optimization Algorithm for Travel Planning

In transport planning, one should allow passengers to travel through the complicated transportation scheme with efficient use of different modes of transport. In this paper, we propose the use of a cockroach swarm optimization algorithm for determining paths with the shortest travel time. In our approach, this algorithm has been modified to work with the time-expanded model. Therefore, we present how the algorithm has to be adapted to this model, including correctly creating solutions and defining steps and movement in the search space. By introducing the proposed modifications, we are able to solve journey planning. The results have shown that the performance of our approach, in terms of converging to the best solutions, is satisfactory. Moreover, we have compared our results with Dijkstra’s algorithm and a particle swarm optimization algorithm.

Use of Different Movement Mechanisms in Cockroach Swarm Optimization Algorithm for Traveling Salesman Problem

This paper presents a new adaptation of the cockroach swarm optimization (CSO) algorithm to effectively solve the traveling salesman problem. Proposed modifications investigate the crossover operators in chase-swarming procedure and directed dispersion of cockroaches. To analyze the benefits of such modifications, the performance of the considered approach is tested on well-known instances. Presented results of all experiments indicate that practical implementation of the CSO algorithm, which includes the sequential constructive crossover (SCX) and 2-opt move is a good approach.

Strategic Planning Optimization Using Tabu Search Algorithm

In this paper, we introduce a method for the optimization of strategic tasks using an approximation algorithm. We propose a mathematical model and suboptimal algorithm for solving this problem near optimally. An overall motivation for the development of the proposed algorithm is discussed with a detailed efficiency analysis. From an end users’ perspective the proposed method has practical applications because it can be used in several applied situations.

Quantum-Inspired Evolutionary Approach for the Quadratic Assignment Problem

The paper focuses on the opportunity of the application of the quantum-inspired evolutionary algorithm for determining minimal costs of the assignment in the quadratic assignment problem. The idea behind the paper is to present how the algorithm has to be adapted to this problem, including crossover and mutation operators and introducing quantum principles in particular procedures. The results have shown that the performance of our approach in terms of converging to the best solutions is satisfactory. Moreover, we have presented the results of the selected parameters of the approach on the quality of the obtained solutions.

A Swarm-Based Approach to Generate Challenging Mazes

Swarm intelligence draws its inspiration from the collective behaviour of many individual agents interacting with both one another and their environment. This paper presents a possibility to apply a swarm-based algorithm, modelled after the behaviour of individuals operating within a group where individuals move around in the manner intended to avoid mutual collisions, to create the most challenging maze developed on a board with determined dimensions. When solving such a problem, two complexity measures are used. Firstly, the complexity of the path was assumed to be a quality criterion, depending on the number of bends and the length of the path between two set points that was subjected to maximisation. Secondly, we focus on the well-known concept of the maze complexity given as the total complexity of the path and all branches. Owing to the uniqueness of the problem, consisting in the maze modification, a methodology was developed to make it possible for the individuals belonging to their population to make various types of movements, e.g., approach the best individual, within the range of visibility, or relocate randomly. The test results presented here indicate a potential prospect of application of the swarm-based methods to generate more and more challenging two-dimensional mazes.

Optimization of Queueing Structures by Firefly Algorithm

In the chapter we describe the application of firefly algorithm in discrete optimization of simple queueing structures such as queueing systems. The optimization of these systems is complicated and there is not any universal method to solve such problem. We briefly cover basic queueing systems. Hence, Markovian systems with exponential service times and a Poisson arrival process with losses, with finite capacity and impatient customers and closed queueing system with finite number of jobs are presented. We consider structural optimization, for example maximization of overall profits and minimizing costs controlled by the number of servers. We show the results of performed experiments.