This article presents an investigation into the development of a multi-objective optimal
chemotherapy control model to reduce the number of cancer cells after a number of fixed …

This paper presents an investigation into the development of an optimal chemotherapy drug
(s) scheduling scheme to control the drug doses to be infused to the patient's body. The …

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 …

Chemotherapy is one of the most prominent cancer treatment modalities. However, it is not
always a comprehensive solution for tumor regression. This led to the advent of novel …

Abstract Model-based optimization using probabilistic modeling of the search space is one
of the areas where research on evolutionary algorithms (EAs) has considerably advanced in …

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 …

DEUM is one of the early EDAs to use Markov Networks as its model of probability
distribution. It uses undirected graph to represent variable interaction in the solution, and …

Intra-patient variability is a key challenge in cancer treatment. This makes it necessary to find
the factors affecting tumor growth and accordingly schedule therapies over the treatment …

This article studies the suitability of modern population based algorithms for designing
combination cancer chemotherapies. The problem of designing chemotherapy schedules is …

In this paper, a design method for optimal cancer chemotherapy schedules via genetic
algorithm (GA) is presented. The design targets the key objective of chemotherapy to …