for the rural population, an improvement in the income of the agriculture and allied sectors is essential for improving the welfare, rural economic prosperity, and the overall economic development. the objective of this study was to determine the optimal pattern in various activities of forest fringe villagers of hezarjarib area in 2013 for management of resources and rural development planning...

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 ...

0360-8352/$ see front matter 2012 Elsevier Ltd. A http://dx.doi.org/10.1016/j.cie.2012.08.005 ⇑ Corresponding author. Tel.: +886 3 2118800x3713 E-mail addresses: [email protected] (C.-T. (H.-M. Chen), [email protected], (Z.-Y. Zhuang). The multi-segment goal programming (MSGP) model is an extension model of GP wherein the core thinking is inherited from the multi-choice goal program...

Abstract Genetic Programming (GP) is a popular and powerful evolutionary optimization algorithm that has wide range of applications such as symbolic regression, classification program synthesis. However, existing GPs often ignore the intrinsic structure ground truth equation regression problem. To improve search efficacy GP on problems by fully exploiting information, this paper proposes geneti...

GP (for Graph Programs) is a rule-based, nondeterministic programming language for solving graph problems at a high level of abstraction, freeing programmers from handling low-level data structures. The core of GP consists of four constructs: single-step application of a set of conditional graph-transformation rules, sequential composition, branching and iteration. This paper gives an overview ...

This paper describes a classification method for on-line handwritten digits based on off-line image representations. The goal is to use image-based features to improve classifier accuracy for on-line handwritten input. In this paper we describe an initial framework that can be used to achieve this goal. This framework for handwritten digit classification is based on genetic programming (GP). Se...

Truncated sharp crested weirs are used to measure flow rate and control upstream water surface in irrigation canals and laboratory flumes. The main advantages of such weirs are ease of construction and capability of measuring a wide range of flows with sufficient accuracy. Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for estimation of hydraulic data. In...

Evolutionary Algorithms (EAs) are routinely applied to solve a large set of optimization problems. Traditionally, their performance in solving those problems is analyzed using the fitness quality and computing time, effect evolutionary operators on both metrics used compare different versions EAs. Nevertheless, scientists face nowadays challenge considering energy efficiency addition computatio...

ABSTRACT This research mainly aims to provide a practical method (1) rank firm's customers, (2) determine the implied uncertainty for customers’ demand, and (3) allocate supply chain (SC) resources meeting customer demands in an equitable manner order them with appropriate/desired level of responsiveness. The suggested methodology utilizes analytic hierarchy process (AHP) Delphi assess customer...

This paper proposes a genetic programming system (GPS) to both predict and program deep beam strength. The soft prediction is to provide estimated results for problems and the soft programming is to represent problems with meaningful formulas. In proposed GPS, two models of genetic programming (GP) and weighted genetic programming (WGP) are involved. GP is structured of a tree topology, inputs,...