Abstract
Manufacturing environments require a real-time adaptation and optimization method to dynamically and intelligently maintain the current scheduling plan feasible. This way, the organization keeps clients satisfied and achieves its objectives (costs are minimized and profits maximized). This paper proposes an optimization approach - Selection Constructive based Hyper-heuristic for Dynamic Scheduling - to deal with these dynamic events, with the main goal of maintaining the current scheduling plan feasible and robust as possible. The development of this dynamic adaptation approach is inspired on evolutionary computation and hyper-heuristics. Our empirical results show that a selection constructive hyper-heuristic could be advantageous on solving dynamic adaptation optimization problems. © 2015 AISTI.

Abstract
User modelling has become a central subject for anybody interested in understanding how users interact with technology. Personalization is a key issue in an era when there is so much information and so many people interacting in so many ways. Modern users desire a customized experience that adapts itself to their requirements and understands what they need even before they notice it. In order to morph any system into an adapting one, every relevant interaction with its users has to be maintained. Then, a mathematical structure capable of discovering patterns amongst that information is necessary, being able to classify users according to the roles they play. With a correct user categorization, the system knows when, how and what to do to adapt its content, via a mixed-initiative approach. In this paper, an artificial neural network is selected as classifier and users are divided in three roles, from beginners to experts. ADSyS, the target system of this proposal, adapts its content based on who is operating it, providing a higher usability. This guide on how to adapt a system to its users is built as part of ADSyS, but is intended to be generalized as a foundation to other systems. © 2015 AISTI.

Abstract
Global competition and the customers demand for customized products with shorter due dates, marked the introduction of the Extended Enterprise. In this Extended Manufacturing Environment (EME), lean, virtual, networked and distributed enterprises collaborate to respond to the market demands. In this paper we study the influence of the batch size on Flexible Flow Shop makespan minimization problem FFC||Cmax for two multi-sites approaches, the FSBF (Flow Shop Based Factories) and the PMBF (Parallel-Machines Based Factories). The computational study demonstrates how the performance of the PMBF model decreases with the increase of batch size and determines the batch sizes in which the performance is similar. © 2015 AISTI.

Abstract
Metaheuristics are very useful to achieve good solutions in reasonable execution times. Sometimes they even obtain optimal solutions. However, to achieve near-optimal solutions, the appropriate tuning of parameters is required. This paper presents a Racing based learning module proposal for an autonomous parameter tuning of Metaheuristics. After a literature review on Metaheuristics parameter tuning and Racing approaches, the learning module is presented. A computational study for the resolution of the Scheduling problem is also presented. Comparing the preliminary obtained results with previous published results allow to conclude about the effectiveness and efficiency of this proposal.

Abstract
Developments in advanced autonomous production resources have increased the interest in the Single-Machine Scheduling Problem (SMSP). Until now, researchers used SMSP with little to no practical application in industry, but with the introduction of multi-purpose machines, able of executing an entire task, such as 3D Printers, replacing extensive production chains, single-machine problems are becoming a central point of interest in real-world scheduling. In this paper we study how simple, easy to implement, Just-in-Time (JIT) based, constructive heuristics, can be used to optimize customer and enterprise oriented performance measures. Customer oriented performance measures are mainly related to the accomplishment of due dates while enterprise-oriented ones typically consider other time-oriented measures. © 2015 AISTI.

Abstract
In the fiercely competitive era induced by expansion of open business archetypes, the managerial aspects of Extended Manufacturing Environments (EMEs) are experiencing growing concerns. There is no scope of leaving a possible operational improvement unexplored. For enhanced operational efficiency and capacity utilization the balancing and scheduling problems of EMEs are, therefore, rightfully considered and an integer programme is proposed in this paper. The model is designed in a spread sheet and solved through What'sBest optimizer. The model capabilities is assessed through a test problem. The results have demonstrated that the model is capable of defining optimized production schedules for EMEs. © 2015 AISTI.