There is a growing demand for multiple output prediction methods capable of both minimizing residual errors and capturing the joint distribution of the response variables in a realistic and consistent fashion. Unfortunately, current methods are designed to optimize one of the two criteria, but not both. This paper presents a framework for multiple output regression that preserves the relationsh...

In this article, we propose compromise allocations for multivariate stratified random sampling using the auxiliary attributes under non-response. We modified extended lexicographic goal programming technique and compared it with fuzzy goal programming and value function technique. We addressed the problem of compromise allocation when the auxiliary information is in the form of an auxiliary att...

This paper presents a method to solve a linear or nonlinear Fuzzy Multiobjective Programming problem. We propose Genetic Search based approaches to the case in which fuzzy constraints are assumed.

    Supplier selection,   Multi-objective decision making,   Fuzzy Compromise programming,   Supply chain management,   Quantity discount .   Supplier selection is naturally a complex multi-objective problem including both quantitative and qualitative factors. This paper deals with this issue from a new view point. A quantity discount situation, which plays a role of motivator for buyer, is con...

Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. ‎‎Standard DEA models are ‎‎quite limited models‎, ‎in the sense that they do not consider a DMU ‎‎at different times‎. ‎To resolve this problem‎, ‎DEA models with dynamic ‎‎structures have been proposed‎.‎In a recent pape...

A Geometric programming (GP) is a type of mathematical problem characterized by objective and constraint functions that have a special form. Many methods have been developed to solve large scale engineering design GP problems. In this paper GP technique has been used to solve multi-objective GP problem as a vector optimization problem. The duality theory for lexicographic geometric programming ...

Visual analytics is a human-machine collaboration to data modeling where extraction of the most informative features plays an important role. Although feature extraction is a multi-objective task, the traditional algorithms either only consider one objective or aggregate the objectives into one scalar criterion to optimize. In this paper, we propose a Pareto-based multi-objective approach to fe...

We model document summarization as a nonlinear 0-1 programming problem where an objective function is defined as Heronian mean of the objective functions enforcing the coverage and diversity. The proposed model implemented on a multi-document summarization task. Experiments on DUC2001 and DUC2002 datasets showed that the proposed model outperforms the other summarization methods. Index Terms – ...

Bounding constraints are used to bound the tolerance of solutions under certain undesirable features. Standard solvers propagate them one by one. Often times, it is easy to satisfy them independently, but difficult to satisfy them simultaneously. Therefore, the standard propagation methods fail. In this paper we propose a novel approach inspired in multi-objective optimization. We compute a mul...