This paper presents a methodology for using heuristic search methods to optimise cancer
chemotherapy. Specifically, two evolutionary algorithms-Population Based Incremental …

Antibiotic resistance is one of the major challenges we face in modern times. Antibiotic use,
especially their overuse, is the single most important driver of antibiotic resistance. Efforts …

Industrial software often has many parameters that critically impact performance. Frequently,
these are left in a sub-optimal configuration for a given application because searching over …

The main objective of multi-modal optimization is to find multiple global and local optima for
a problem in only one execution. Detecting multiple solutions to a multi-modal optimization …

Cancer is a serious and often fatal disease, widespread in the developed world. One of the
most common methods of treating cancer is chemotherapy with toxic drugs. These drugs …

Chemotherapy treatment for cancer is a complex optimisation problem with a large number
of interacting variables and constraints. A number of different heuristics have been applied …

Purpose–Although genetic algorithm (GA) has already been extended to various types of
engineering problems, tuning its parameters is still an interesting field of interest. Some …

Genetic algorithms have already been applied to various fields of engineering problems as
a general optimization tool in charge of expensive sampling of the coded design space. In …

Background Parallel computing is a powerful way to reduce computation time and to
improve the quality of solutions of evolutionary algorithms (EAs). At first, parallel EAs (PEAs) …

A well-known paradigm for optimisation is the evolutionary algorithm (EA). An EA maintains
a population of possible solutions to a problem which converges on a global optimum using …