This paper analyzes a proposed release control methodology, WIPLOAD Control (WIPLCtrl), using a transfer line case modeled by Markov process modeling methodology. The performance of WIPLCtrl is compared with that of CONWIP under 13 system configurations in terms of throughput, average inventory level, as well as average cycle time. As a supplement to the analytical model, a simulation model of ...

Background: Given importance to learning and given priority to this point that human beings acquire more of their abilities and competencies through learning, learning styles are focused as a pivotal factor in realization of mental and potential abilities. Empowering academic members in the areas of teaching, scholarship, and leadership leads to the achievement of the missions and goals of the ...

This work represents the first step towards a task library system in the reinforcement learning domain. Task libraries could be useful in speeding up the learning of new tasks through task transfer. Related transfer can increase learning rate and can help prevent convergence to sub-optimal policies in reinforcement learning. Unrelated transfer can be extremely detrimental to the learning rate. ...

transfer learning allows the knowledge transference from the source (training dataset) to target (test dataset) domain. feature selection for transfer learning (f-mmd) is a simple and effective transfer learning method, which tackles the domain shift problem. f-mmd has good performance on small-sized datasets, but it suffers from two major issues: i) computational efficiency and predictive perf...

This paper examines and compares various manufacturing policies which manufacturer may adopt so as to improve the performance of a vendor managed inventory (VMI) partnership. The goal is to maximize the combined cumulative profit of supply chain while minimizing relevant inventory management costs. The supply chain is a two-level system with a single manufacturer and single retailer at each lev...

A result in the Bayesian inventory management literature is: If lost sales are not observed, the Bayesian optimal inventory level is larger than the myopic inventory level (one should “stock more” to learn about the demand distribution). This result has been proven in other studies under the assumption that inventory is perishable, so the myopic inventory level is equal to the Bayesian optimal ...

The use of Enterprise Resource Planning system in manufacturing companies aims to increase the companies’ productivity. In this case, an integrated ERP could maximize production. Thus, researcher conducted a study that discussed application Odoo V12.0 chicken company. This research focused on inventory sectors. There is no special manage section. business process reengineering has been done wer...

We participated in the SemEval-2007 coarse-grained English all-words task and fine-grained English all-words task. We used a supervised learning approach with SVM as the learning algorithm. The knowledge sources used include local collocations, parts-of-speech, and surrounding words. We gathered training examples from English-Chinese parallel corpora, SEMCOR, and DSO corpus. While the fine-grai...

Reinforcement learning (RL) appeals to many researchers in recent years because of its generality. It is an approach to machine intelligence that learns to achieve the given goal by trial-and-error iterations with its environment. This paper proposes a case-based reinforcement learning algorithm (CRL) for dynamic inventory control in a multi-agent supply-chain system. Traditional time-triggered...

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