This paper presents a new method that effectively determines a Pareto front for biobjective optimization with potential application to multiple objectives. A traditional method for multiobjective optimization is the weighted sum method, which seeks Pareto optimal solutions one by one by systematically changing the weights among the objective functions. Previous research has shown that this meth...

Communications satellites are designed to provide services by forwarding signals to customers. Uplink signals are filtered and amplified to ensure signal output quality. This is ensured by the payload part of the satellite. Reconfigurable hardware components like switches are embedded in the payload to route signals through the satellite. By setting switch positions, satellite engineers are abl...

In the pharmaceutical industry, clinical trials constitute a critically important and very expensive part of the new drug development process. A clinical trial supply chain will terminate after 1-2 years, and leftovers at the end of clinical trials constitute an important financial cost since all the unused materials should be disposed after clinical trial completion. Normally, extra safety sto...

We consider constrained biobjective optimization problems. One of the extant issues in this area is that of uniform sampling of the Pareto front. We utilize equispacing constraints on the vector of objective values, as discussed in a previous paper dealing with the unconstrained problem. We present a direct and a dual formulation based on arc-length homotopy continuation and illustrate the dire...

In a multimodal optimization task, the main purpose is to find multiple optimal solutions (global and local), so that the user can have better knowledge about different optimal solutions in the search space and as and when needed, the current solution may be switched to another suitable optimum solution. To this end, evolutionary optimization algorithms (EA) stand as viable methodologies mainly...

This paper presents a meta-objective optimization approach, called Bi-Goal Evolution (BiGE), to deal with multi-objective optimization problems with many objectives. In multi-objective optimization, it is generally observed that 1) the conflict between proximity and diversity requirements is aggravated with the increase of the number of objectives and 2) the Pareto dominance loses its effective...

Pareto local search (PLS) is an extension of iterative improvement methods for multi-objective combinatorial optimization problems and an important part of several state-of-the-art multi-objective optimizers. PLS stops when all neighbors of the solutions in its solution archive are dominated. If terminated before completion, it may produce a poor approximation to the Pareto front. This paper pr...

In order to solve the two-sided matching problem based on uncertain score information, a new method is presented. Firstly, the description of the two-sided matching problem with uncertain scores is given. Secondly, the satisfaction degrees of each agent towards the agents on the other side are calculated. A multi-objective optimization model to maximize the satisfaction degrees of agents is set...