Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives.

Second, the conversion to a single-objective optimization problem involves additional constraints. Third, since most real-world goal programming problems involve nonlinear criterion functions, the ...

Xiaoseng Zhang, Multi-objective Optimization Design in Construction Period Considering the Influence of Marine Climate, Journal of Coastal Research, SPECIAL ISSUE NO. 115. Advances in Water Resources, ...

Other algorithms, such as the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), break the optimization problem into smaller sub-problems, each representing a weighted combination ...

There are several optimization techniques available in PROC NLMIXED. You can choose a particular optimizer with the TECH=name option in the PROC NLMIXED statement. No algorithm for optimizing general ...