The best performing methods for Dynamic Optimization Problems (DOPs) are usually based on a set of agents that can have different complexity (like solutions in Evolutionary Algorithms, particles in Particle Swarm Optimization, or metaheuristics in hybrid cooperative strategies). While methods based on low-complexity agents are widely applied in DOPs, the use of more “intelligent” agents has rar...

The multipopulation method has been widely used to solve dynamic optimization problems (DOPs) with the aim of maintaining multiple populations on different peaks to locate and track multiple changing optima simultaneously. However, to make this approach effective for solving DOPs, two challenging issues need to be addressed. They are how to adapt the number of populations to changes and how to ...

In recent years, there has been a growing interest in addressing dynamic optimization problems (DOPs) using evolutionary algorithms (EAs). Several approaches have been developed for EAs to increase the diversity of the population and enhance the performance of the algorithm for DOPs. Among these approaches, immigrants schemes have been found beneficial for EAs for DOPs. In this paper, random, e...

Ant colony optimization (ACO) algorithms have proved that they can adapt to dynamic optimization problems (DOPs) when they are enhanced to maintain diversity. DOPs are important due to their similarities to many real-world applications. Several approaches have been integrated with ACO to improve their performance in DOPs, where memory-based approaches and immigrants schemes have shown good resu...

Usually, discrete optimization problems (DOPs) from applications have a special structure, and the matrices of constraints for largescale problems have a lot of zero elements (sparse matrices). One of the promising ways to exploit sparsity in the interaction graph of the DOP is nonserial dynamic programming (NSDP), which allows to compute a solution in stages such that each of them uses results...

To understand the mechanism of Saposin C-membrane binding at low pH, several molecular dynamics (MD) simulations of saposin C with 1,2-dioleoyl-sn-glycero-3-phosphatidylserine (DOPS 18; 1) or modified DOPS were performed in the default charge states at neutral pH or, based on the pKa calculations, with some protonated acidic residues to approximate low pH conditions. It was found that the elect...

Many real discrete optimization problems (DOPs) are NP -hard and contain a huge number of variables and/or constraints that make the models intractable for currently available solvers. Large DOPs can be solved due to their special structure using decomposition approaches. An important example of decomposition approaches is tree decomposition with local decomposition algorithms using the special...

Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when they are enhanced to maintain diversity and transfer knowledge. Several approaches have been integrated with ACO to improve its performance for DOPs. Among these integrations, the ACO algorithm with immigrants schemes has shown good results on the dynamic travelling salesman pro...

Multimodal tumor imaging with targeted nanoparticles potentially offers both enhanced specificity and sensitivity, leading to more precise cancer diagnosis and monitoring. We describe the synthesis and characterization of phenol-substituted, lipophilic orange and far-red fluorescent dyes and a simple radioiodination procedure to generate a dual (optical and nuclear) imaging probe. MALDI-ToF ana...