Abstract
The ability to select the most appropriate materials for a given application is the fundamental challenge faced by a design engineer. The objective of any material selection procedure is to identify appropriate selection criteria and to obtain the most appropriate combination of criteria in conjunction with requirements. Hence, selection of material is a multicriteria decision making problem. This study investigates and evaluates critical material selection criteria in a priority framework using the fuzzy Delphi-analytical hierarchy process method to overcome all shortcomings from AHP and Delphi methods that are common in material selection problem. 75 of the most important criteria for material selection have been collected from the literature. These criteria have been questioned in automobile interior design firms in Iran for car dashboard design. This ranking method would help product designers to decide on appropriate materials in a consistent method. Results indicate that "general" criteria such as availability, quality, risk, and technology are the most important criteria from the viewpoint of Iranian car manufacturers. Other criteria such as financial, technical, social and environmental, and sensorial criteria are relatively important in subsequent ranks.

Abstract
There is growing evidence that internationalization of small and medium enterprises (SMEs) has become a priority to gain competitive advantage. However, SMEs still face major challenges and obstacles during these processes. This paper proposes a model of collaborative networks for internationalization processes of SMEs, mediated by industrial enterprise associations (IEAs), in order to improve decision-making processes. First, a systematic literature review (SLR) was performed to study the impact that networks and collaboration have in the decision-making process of internationalization. Then, the model was developed using adequate information and knowledge management tools. Finally, to understand the relevance of the proposed model, data were gathered through interviews to key persons in companies of the IT/electronics and textile industries. Results showed that collaborative networks can represent an important facilitator in the internationalization of SMEs and that IEAs can have a fundamental role for promoting collaboration in this domain, between associated SMEs.

Abstract
Production planning and scheduling in the process industry in general and in the pulp and paper (P&P) sector in particular can be very challenging. Most practitioners, however, address those activities relying only on spreadsheets, which is time-consuming and sub-optimal. The literature has reported some decision support systems (DSSs) that are far from the state-of-the-art with regard to optimization models and methods, and several research works that do not address industrial issues. We contribute to reduce that gap by developing and describing a DSS that resulted from several iterations with a P&P company and from a thorough review of the literature on process systems engineering. The DSS incorporates relevant industrial features (which motivated the development of a specific model), exhibits important technical details (such as the connection to existing systems and user-friendly interfaces) and shows how optimization can be integrated in real world applications, enhanced by key pre- and post-optimization procedures.

Abstract
Lot sizing and scheduling by mixed integer programming has been a hot research topic in the last 20 years. Researchers have been trying to develop stronger formulations, as well as to incorporate real-world requirements from different applications. In this paper we illustrate some of these requirements and show howmodels have been adapted and extended. Motivation comes from different industries, especially from process and fast moving consumer goods industries.

Abstract
Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Abstract
Sectorization means dividing a whole into parts (sectors), a procedure that occurs in many contexts and applications, usually to achieve some goal or to facilitate an activity. The objective may be a better organization or simplification of a large problem into smaller sub-problems. Examples of applications are political districting and sales territory division. When designing/comparing sectors some characteristics such as contiguity, equilibrium and compactness are usually considered. This paper presents and describes new generic measures and proposes a new measure, desirability, connected with the idea of preference. © 2015, Springer International Publishing Switzerland.