In many real-world applications, the problem arises that several objectives have to be optimized concurrently leading to a multi-objective optimization problem. Since these goals are typically contradictory, it comes as no surprise that the solution set— the so-called Pareto set—of such problems does (in general) not consist of one single solution. Moreover, under some mild conditions, this set...

We consider a wireless communication system in which N transmitter-receiver pairs want to communicate with each other. Each transmitter transmits data at a certain rate using a power that depends on the channel gain to its receiver. If a receiver can successfully receive the message, it sends an acknowledgement (ACK), else it sends a negative ACK (NACK). Each user aims to maximize its probabili...

We analyze the Pareto efficiency, or inefficiency, of solutions to routing games and load balancing games, focusing on Nash equilibria and greedy solutions to these games. For some settings, we show that the solutions are necessarily Pareto optimal. When this is not the case, we provide a measure to quantify the distance of the solution from Pareto efficiency. Using this measure, we provide upp...

In this study criterion of maximum profit intensity for transportation problems, in contrast to the known criteria of minimum expenses or minimum time for transportation, is considered. This criterion synthesizes financial and time factors and has real economic sense. According to the purpose of this paper, the algorithm of the solution of such a transportation problem is constructed. It is sho...

abstract: in this paper, optimization of boeing 747 wing has been accomplished for cruise condition (mach number=0.85, flight altitude=35000 ft), where an optimal wing shape is proposed. objective functions are minimization of wing weight and drag force that as well as confining design parameters, two functional constrains are applied. the first functional constrain is fuel tank volume in the a...

This work presents a new learning scheme for improving generalization of Multilayer Perceptrons (MLPs). The proposed Multi-objective algorithm (MOBJ) approach minimizes both the sum of squared error and the norm of network weight vectors to obtain the Pareto-optimal solutions [1]. Preliminar results are shown in [3]. Since the Pareto-optimal solutions are not unique, we need a decision phase in...

Decomposition-based methods are often cited as the solution to multi-objective nonconvex optimization problems with an increased number of objectives. These methods employ a scalarizing function to reduce the multi-objective problem into a set of single objective problems, which upon solution yield a good approximation of the set of optimal solutions. This set is commonly referred to as Pareto ...

In this paper, an efficient transmit beam design and user scheduling method is proposed for multi-user (MU) multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) downlink, based on Pareto-optimality. The proposed beam design and user scheduling method groups simultaneously-served users into multiple clusters with practical two users in each cluster, and then applies spatical...

Pareto-optimal solutions are one of the most important and well-studied solution concepts in multi-objective optimization. Often the enumeration of all Pareto-optimal solutions is used to filter out unreasonable trade-offs between different criteria. While in practice, often only few Pareto-optimal solutions are observed, for almost every problem with at least two objectives there exist instanc...