Evolutionary Method Engineering - A Case Study in Meta
نویسندگان
چکیده
Meta modeling is a widely established means for developing conceptual modeling methods (CMM). Here, we show how a CMM for the structured conceptual design of management information systems has been developed in an evolutionary process based on meta modeling. The aim of management information systems is to satisfy the information need managers have to successfully accomplish their tasks. The quality of management decisions is highly dependent on the information they are based on. A structured conceptual design of management information systems is a crucial task that has to precede their implementation and monitoring. Several conceptual modeling methods have been developed in order to support the specification of data warehouse structures and management information systems. However, none of them was found to be appropriate to bridge the communication gap in the process of requirements analysis. Thus, in an ongoing research effort, a CMM has been designed to adequately support the conceptual design of management information systems. ' Several case studies were conducted and in an iterative process the findings were incorporated to improve the initial CMM. The result of this process is a CMM quite different to the original one. The aim of this paper is to elaborate on the evolutionary development of a CMM using meta modeling and to show how it has successfully been applied in multiple case studies.
منابع مشابه
A multi-objective evolutionary approach for integrated production-distribution planning problem in a supply chain network
Integrated production-distribution planning (PDP) is one of the most important approaches in supply chain networks. We consider a supply chain network (SCN) to consist of multi suppliers, plants, distribution centers (DCs), and retailers. A bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in ...
متن کاملDesigning a Meta-Heuristic Algorithm Based on a Simple Seeking Logic
Nowadays, in majority of academic contexts, it has been tried to consider the highest possible level of similarities to the real world. Hence, most of the problems have complicated structures. Traditional methods for solving almost all of the mathematical and optimization problems are inefficient. As a result, meta-heuristic algorithms have been employed increasingly during recent years. In thi...
متن کاملConsolidated Technique of Response Surface Methodology and Data Envelopment Analysis for setting the parameters of meta-heuristic algorithms - Case study: Production Scheduling Problem
In this study, given the sequence dependent setup times, we attempt using the technique of Response Surface Methodology (RSM) to set the parameters of the genetic algorithm (GA), which is used to optimize the scheduling problem of n job on 1 machine (n/1). It aims at finding the most suitable parameters for increasing the efficiency of the proposed algorithm. At first, a central composite d...
متن کاملSIZING OPTIMIZATION OF TRUSS STRUCTURES WITH NEWTON META-HEURISTIC ALGORITHM
This study is devoted to discrete sizing optimization of truss structures employing an efficient discrete evolutionary meta-heuristic algorithm which uses the Newton gradient-based method as its updating scheme and it is named here as Newton Meta-heuristic Algorithm (NMA). In order to enable the NMA population-based meta-heuristic to effectively explore the discrete design space, a term contain...
متن کاملAn Energy-efficient Mathematical Model for the Resource-constrained Project Scheduling Problem: An Evolutionary Algorithm
In this paper, we propose an energy-efficient mathematical model for the resource-constrained project scheduling problem to optimize makespan and consumption of energy, simultaneously. In the proposed model, resources are speed-scaling machines. The problem is NP-hard in the strong sense. Therefore, a multi-objective fruit fly optimization algorithm (MOFOA) is developed. The MOFOA uses the VIKO...
متن کاملPrediction of Surface Roughness by Hybrid Artificial Neural Network and Evolutionary Algorithms in End Milling
Machining processes such as end milling are the main steps of production which have major effect on the quality and cost of products. Surface roughness is one of the considerable factors that production managers tend to implement in their decisions. In this study, an artificial neural network is proposed to minimize the surface roughness by tuning the conditions of machining process such as cut...
متن کامل