Evolutionary algorithms (EAs) are a highly successful tool commonly used in practice to solve algorithmic problems. This remarkable practical value, however, is not backed up by a deep theoretical understanding. Such an understanding would facilitate the application of EAs to further problems. Runtime analyses of EAs are one way to expand the theoretical knowledge in this field. This thesis pre...

Throughout the history, Genetic Algorithms (GA) have been widely applied to a broad range of combinatorial optimization problems. Its easy applicability to areas such as transport or industry has been one of the reasons for its great success. In this paper, we propose a new Adaptive Multi-Crossover Population Algorithm (AMCPA). This new technique changes the philosophy of the basic genetic algo...

A compact formulation of the set of tours neither in a graph nor its complement is presented and illustrates a general methodology proposed for constructing polyhedral models of decision problems based upon permutations, projection and lifting techniques. Directed Hamilton tours on n vertex graphs are interpreted as (n-1)- permutations. Sets of extrema of Birkhoff polyhedra are mapped to tours ...

Increasing of net energy storage (Q net) and discharge time of phase change material (t PCM), simultaneously, are important purpose in the design of solar systems. In the present paper, Multi-Objective (MO) based on hybrid of Particle Swarm Optimization (PSO) and multiple crossover and mutation operator is used for Pareto based optimization of solar systems. The conflicting objectives are Q net...

Our ability to solve large, important combinatorial optimization problems has improved dramatically in the decade. The availability of reliable software, extremely fast and inexpensive hardware and high-level languages that make the modeling of complex problems much faster have led to a much greater demand for optimization tools. This paper highlights the major breakthroughs and then describes ...

The knapsack problem is one of the most widely researched NP-complete combinatorial optimization problems and has numerous practical applications. This paper proposes a quantum-inspired differential evolution algorithm with grey wolf optimizer (QDGWO) to enhance diversity convergence performance improve in high-dimensional cases for 0-1 problems. proposed adopts quantum computing principles suc...

Problem statement: Knapsack problem is a typical NP complete problem. During last few decades, Knapsack problem has been studied through different approaches, according to the theoretical development of combinatorial optimization. Approach: In this study, modified evolutionary algorithm was presented for 0/1 knapsack problem. Results: A new objective_func_evaluation operator was proposed which ...

Here we are given a finite connected undirected graph (V,E) (so V is the set of vertices and E the set of edges) and weights on the edges, i.e., c(e) ∈ R for all e ∈ E. The task is to find a set T ⊆ E such that (V, T ) is a (spanning) tree and ∑ e∈T c(e) is minimum. (Recall that a tree is a connected graph without cycles.) The figure below shows on the left a set V of eight points in the Euclid...