The main objective of this paper is to outline a theoretical framework analyse how humans’ decision-making strategies under uncertainty manage the trade-off between information gathering (exploration) and reward seeking (exploitation). A key observation, motivating line research, awareness that human learners are amazingly fast effective at adapting unfamiliar environments incorporating upcomin...

The basis pursuit problem seeks a minimum one-norm solution of an underdetermined least-squares problem. Basis pursuit denoise (BPDN) fits the least-squares problem only approximately, and a single parameter determines a curve that traces the optimal trade-off between the least-squares fit and the one-norm of the solution. We prove that this curve is convex and continuously differentiable over ...

Multi Objective Economic dispatch (MOED) problem has gained recent attention due to the deregulation of power industry and environmental regulations. So generating utilities should optimize their emission in addition to the operating cost. In this paper a Pareto frontier Differential Evolution (PDE) technique is developed to solve MOED problem, which provides a set of feasible solutions to the ...

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...

Decision making in modern forest management planning is challenged by the need to recognize multiple ecosystem services and address preferences goals of stakeholders. This research presents an innovative a posteriori preference modeling multi-objective integer optimization (MOIP) approach encompassing programming models new technique for generation interactive visualization Pareto frontier. Due...

Skyline queries represent a dataset by the points on its pareto frontier, but can become very large. To alleviate this problem, representative skylines select exactly k skyline points. However, existing approaches are not scaleinvariant, not stable, or must materialise the entire skyline. We introduce the maximum coverage representative skyline, which returns the k points collectively dominatin...

This paper examines inability of CCR and BCC models in improving DMU’s scale efficiency when a production possibility frontier is assumed as variable returns to scale. This paper also finds that DEA result can be more efficient than the Pareto-efficiency when a DMU is feasibly projected to be both technically and scale efficient. This feasible projection can only be achieved by a VRS DEA model ...

[1] The operation of large-scale water resources systems often involves several conflicting and noncommensurable objectives. The full characterization of tradeoffs among them is a necessary step to inform and support decisions in the absence of a unique optimal solution. In this context, the common approach is to consider many single objective problems, resulting from different combinations of ...

The NBI-NLPQLP optimization method is tested on several multi-objective optimization problems. Its performance is compared to that of MOGA-II: since NBI-NLPQLP is based on the classical gradientbased NLPQLP, it is fast and accurate, but not as robust, in comparison with the genetic algorithm. Furthermore a discontinuous Pareto frontier can give rise to problems in the NBI’s convergence. In orde...

In this paper we present a model of credit market with several homogeneous lenders competing to finance an investment project. Contracts are non-exclusive, hence the borrower can accept whatever subset of the offered loans. We use the model to discuss efficiency issues in competitive economies with asymmetric information and non-exclusive agreements. We characterize the equilibria of this commo...