Sustainability is a major challenge in any plant factory, particularly those involving precision
agriculture. In this study, an adaptive fertigation system in a three-tier nutrient film technique …

Constrained multi-objective optimization problems (cMOPs) are complex because the
optimizer should balance not only between exploration and exploitation, but also between …

When solving constrained multi-objective optimization problems (CMOPs), multiple
conflicting objectives and multiple constraints need to be considered simultaneously, which …

Local search algorithms are widely applied in solving large-scale Distributed constraint
optimization problems (DCOPs) where each agent holds a value assignment to its variable …

Constrained optimization is a computationally difficult task, particularly if the constraint
functions are nonlinear and non-convex. As a generic classical approach, the penalty …

Evolutionary algorithms are modified in various ways to solve constrained optimization
problems. Of them, the use of a bi-objective evolutionary algorithm in which the minimization …

Nowadays, chemical processes are projected to obtain their best performance in energy and
water consumption, pollutant emissions and total annual costs, while still meeting quality of …

A sequential irrigation scheduling problem is the problem of preparing a schedule to
sequentially service a set of water users. This problem has an analogy with the classical …

The implementation of resource conservation schemes in industry can be enhanced through
the application of systematic design methodologies. In particular, process integration …

A genetic algorithm aiming for finding the global minimum and multiple deep local minima of
a function exhibiting a complex landscape is studied. A feedback dynamic penalty function is …