This paper deals with the utilizing of the Bayesian optimization algorithm (BOA) for multiobjective optimization of hypergraph partitioning. The main attention is focused on the incorporation of the Pareto optimality concept. We have modified the standard algorithm BOA for one criterion optimization according to well known niching techniques to find the Pareto optimal set. This approach was com...

Portfolio Optimization is based on the efficient allocation of several assets, which can get heavily affected by uncertainty in input parameters. So we must look for such solutions give us steady results uncertain conditions too. Recently, optimization problems are being dealt with robust approach. With this development, interest researchers has been shifted toward portfolio optimization. In pa...

During the clinical years, medical students frequently experience physical and mental health problems, which are exacerbated by their work schedules. To address this issue, we develop a bi-objective mathematical model in study. The two objectives of 1) balancing workload each student group 2) minimizing deviation among groups. In addition, includes constraints on ward rotation sequencing. requi...

This document supports the main paper by providing further explanations, results, a worked example, and detailed pseudocode for our optimization techniques. Section 1 explains our lens optimization in detail, which determines optical aspherical lens shapes and complementary focal surfaces given an input lens width size in pixels and the field of view. Section 2 presents our discrete light field...

In this paper we present a novel approach to register multiple scans from a static object. We formulate the registration problem as an optimization of the maps from all other scans to one reference scan where any map between two scans can be represented by the composition of these maps. In this way, all loop closures can be automatically guaranteed as the maps among all scans are globally consi...

This paper proposes a new multi-objective bi-level programming model for the ring road bus lines and fare design problems. The proposed consists of two layers: traffic management operator travelers. In upper level, we propose fares optimization in which operator’s profit travelers’ utility are set as objective functions. lower evolutionary multi agent bounded rational reinforcement learning wit...