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Showing 2 results for Naderi
Bahman Naderi, Vahid Roshanaei,
Volume 1, Issue 1 (5-2014)
Abstract
In some industries as foundries, it is not technically feasible to interrupt a processor between jobs. This restriction gives rise to a scheduling problem called no-idle scheduling. This paper deals with scheduling of no-idle open shops to minimize maximum completion time of jobs, called makespan. The problem is first mathematically formulated by three different mixed integer linear programming models. Since open shop scheduling problems are NP-hard, only small instances can be solved to optimality using these models. Thus, to solve large instances, two meta-heuristics based on simulated annealing and genetic algorithms are developed. A complete numerical experiment is conducted and the developed models and algorithms are compared. The results show that genetic algorithm outperforms simulated annealing.
Mohammad Mohammadi, Mehrdad Nouri Koupaei, Bahman Naderi,
Volume 3, Issue 1 (5-2016)
Abstract
Nowadays Business intelligence (BI) tools provide optimal decision making, analyzing, controlling and monitoring of operations in enterprise systems like enterprise resource planning (ERP) and mainly refer to strong decision making methods used in online analytical processing, reporting and data analysis, such as improve internal processes, analysis of resources, information needs analysis, reduce costs and increase revenue. The main purpose of paper is creating a unified framework for the application of BI in ERP systems which results of value-added inflexible manufacturing systems (FMS). In this paper, business process system and interaction between technology and environment byapplying BI in ERPsystems of companies that use flexible manufacturing systems have been presented. This paper is a comprehensive review of recent literature that examined the effects of BI systems on the fourlevels of Tenhialaet al.\' Model (2015).This model based on cross-sectional data from 151 manufacturing plants proved that ERP is essential for the FMS. According to results of this paper, the answer to this question is important “How can we use the potential data, and intelligence of BI in ERP systems for the effective flexible manufacturing systems?” This study has four hypotheses to answer this question and based on results, all four hypotheses were confirmed. Finally, a model has been developed to determine the relationship between BI (as enabler of ERP) and FMS.
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