Duality theory is important in finding solutions to optimization problems. For example, linear programming problems, the primal and dual problem pairs are closely related, i.e., if optimal solution of one known, then for other can be obtained easily. In order an solved through dual, first step formulate its analyze characteristics. this paper, we construct model uncertain multi-objective as wel...

Ab initio pseudopotentials are a linchpin of modern molecular and condensed matter electronic structure calculations. In this work, we employ multi-objective optimization to maximize pseudopotential softness while maintaining high accuracy transferability. To accomplish this, develop formulation in which simultaneously maximized, with determined by the ability reproduce all-electron energy diff...

The conventional layout problem is concerned with finding the arrangements of components inside container to optimize objectives under geometrical constraints, i.e., no component overlap and protrusion. In this paper, multi-objective optimization for balance activity requirements functional constraints developed. Integrating accessibility as ensures maintenance or proper operation. However, add...

The satellites scheduling mission play an effective role in enhancing the of ground station control and monitoring systems. In this search, SGSEO is re-formulated into a multi-objective optimization task. Therefore, Gravitational Search Algorithm GSA exploited to attain several essential objectives for generating tight scheduling. Moreover, particle swarm model PSO consolidated with novel form ...

This chapter is devoted to summarize common concepts related to multi-objective optimization (MO). An overview of “traditional” as well as CI-based MO is given. Further, all aspects of performance assessment for MO techniques are discussed. Finally, challenges facing MO techniques are addressed. All of these description and analysis give the readers basic knowledge for understandings the rest o...