Our genetic heritage is not a blueprint or an algorithm, as many biologists have imagined, but something else entirely.

A steady-state \(\mu\)GA-based generative hyper-heuristic approach for producing selection hyper-heuristics that outperform those generated by other evolutionary methods in the literature for the ...

Abstract: The 0-1 Knapsack Problem (KP) and Bin Packing Problem (BPP) are NP-hard combinatorial optimization challenges often tackled using metaheuristics. Both problems have prominent utilization in ...

An algorithm is present in everything in your life! No, it's not spying on you, nor is it a monster in the closet! But don't panic, everything is under control! An algorithm is a series (a ...

The 3D bin packing problem is a challenging combinatorial optimization problem with numerous real-world applications. In this paper, we present a novel approach for solving this problem by integrating ...

Multi-objective scheduling problems in workshops are commonly encountered challenges in the increasingly competitive market economy. These scheduling problems require a trade-off among multiple ...

Two-dimensional (2D) irregular packing problems are widespread in manufacturing industries such as shipbuilding, metalworking, automotive production, aerospace, clothing and furniture manufacturing.

Implementation of simulated annealing algorithm for the multiple choice multidimensional knapsack problem. The multiple choice knapsack problem has n groups of items and m constraints. The objective ...

[Ahuja00] “A greedy genetic algorithm for the quadratic assignment problem”, R. Ahuja, J. Orlin, A. Tiwari, Computers and Operations Research, vol. 27, issue 10 (Sept. 2000), 917--934, ACM (2000) ...

The ancient philosopher Confucius has been credited with saying “study your past to know your future.” This wisdom applies not only to life but to machine learning also. Specifically, the availability ...