We use heuristics to solve computationally difficult problems where optimal solutions are too expensive to deploy, hard to manage, or otherwise inefficient. Our prior work, MetaOpt, shows many of the ...

Identified and explained in detail the gaps and possible future works for improvement in two popular research papers that used heuristic and meta-heuristic algorithms to solve multi-objective vehicle ...

Abstract: The Travelling Salesman Problem (TSP) is a well known method for the optimisation problem that asks you to find the shortest route that visits each city in a set exactly once and then goes ...

A group of researchers have developed an algorithm designed to prevent threat actors from disrupting quantum communication channels across an entire network. Researchers from Italy's Politecnico di ...

ABSTRACT: To effectively evaluate a system that performs operations on UML class diagrams, it is essential to cover a large variety of different types of diagrams. The coverage of the diagram space ...

Abstract: Driven by an unprecedented surge in freight transportation and city logistics, this paper tackles a practical variant of the famous Vehicle Routing Problem that jointly accounts for the ...

This project aimed to implement three well-known meta-heuristic algorithms: cuckoo search (CS), bat algorithm (BA), and flower pollination algorithm (FPA). We found that three algorithms could have a ...

The binary paint shop problem (BPSP) is an APX-hard optimization problem of the automotive industry. In this work, we show how to use the quantum approximate optimization algorithm (QAOA) to find ...