Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative
way to tackle complex and dynamic problems in urban studies. The goal of this article is a …

Agricultural landscapes presently cover about 46% of earth terrestrial surface. This
cultivated area is decreasing, whereas the global food demand is projected to increase up to …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

A spatial multi-objective land use optimization model defined by the acronym 'NSGA-II-
MOLU'or the 'non-dominated sorting genetic algorithm-II for multi-objective optimization of …

As a result of multiple land use types, spatial heterogeneity, and conflicts of interest among
multiple participants, multi-site land use allocation becomes a complex and significant …

Urban land use spatial allocation is crucial to lots of countries that are usually under severe
environmental and demographic pressures, because it can be used to alleviate some land …

Optimizing land use allocation is a challenging task, as it involves multiple stakeholders with
conflicting objectives. In addition, the solution space of the optimization grows exponentially …

Computer-based agricultural decision support systems (aDSS) may be argued to have
passed sequentially through phases of unbelief, euphoria and disappointment, and to be …

Pastoral systems are characterised by a number of features that are absent in arable
crop** systems. These features include:(i) pastures are biologically diverse so interactions …

The Pareto front can provide valuable information on land-use planning decision by
revealing the possible trade-offs among multiple, conflicting objectives. However, seeking …