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Planning and scheduling are forms of decision making, which play a crucial role in manufacturing as well as in service industries. In the current competitive environment, effective sequencing and scheduling has become a necessity for survival in the marketplace. A great challenge for today’s companies is not only how to adapt to this changing, competitive business environment but also how to draw a competitive advantage from the way in which they choose to do so. Intelligent solutions, based on expert systems, to solve problems in the field of production planning and scheduling are becoming more and more widespread nowadays. Proposes an expert system, which uses the prevailing conditions in the industrial environment in order to select and “fire” dynamically the most appropriate scheduling algorithm from a library of many candidate algorithms.

In this paper we consider the use of ontologies as the basis for structuring and simplifying the process of constructing real‐time problem‐solving tools, focusing specifically on the task of production scheduling. In spite of the commonality in production scheduling system requirements and design, different scheduling environments invariably present different challenges (e.g. different constraints, different objectives, different domain structure, etc.). The proposed methodology for building ontologies used for production scheduling systems represents a synthesis of extensive work in developing constraint‐based scheduling models for a wide range of applications in manufacturing and production planning. Since the effective modeling is one of the most important and difficult steps in the development of reliable information systems, and taking into consideration the fact that the general problem of the production scheduling in the industries is very difficult and still unsolved, one can easily estimate the merit of this methodology.

In the current competitive environment, each company faces a number of challenges: quick response to customers’ demands, high quality of products or services, customers’ satisfaction, reliable delivery dates, high efficiency, and others. As a result, during the last five years many firms have proceeded to the adoption of enterprise resource planning (ERP) solutions. ERP is a packaged software system, which enables the integration of operations, business processes and functions, through common data‐processing and communications protocols. However, the majority, if not all, of these systems do not support the production scheduling process that is of crucial importance in today’s manufacturing and service industries. In this paper, the authors propose a knowledge‐based system for production‐scheduling that could be incorporated as a custom module in an ERP system. This system uses the prevailing conditions in the industrial environment in order to select dynamically and propose the most appropriate scheduling algorithm from a library of many candidate algorithms.

Presents the NUMASS Web‐based system, which was developed for the needs of the European Commission (designed to be used mainly by AIDCO‐A5). Its main objective is to improve the management and monitoring of Tacis Nuclear Safety Programme, by showing in a graphical way the progress of projects/works and prompting for corrective actions.

It is common knowledge that during the last decade markets have become extremely competitive with product variety increasing continuously and product life cycles shortening. Many manufacturing companies, which hitherto satisfied their customers while operating specific production systems, were recently obliged to reconsider because of the potential superiority of other “manufacturing philosophies”. In the literature, we meet a great variety of production systems and manufacturing philosophies, while, on the other side, in industry we usually find different combinations of “primary” productions systems. In this paper, we present the existing “state‐of‐the‐art” theoretical and experiential knowledge about productions systems, as well as describe their basic characteristics in a useful, exact and comprehensive way for practitioners and software houses who want to have a knowledge base for further research and practical implementation in the wider field of production management, planning and scheduling.

The purpose of this paper is to assess the relationship between service quality, customer satisfaction and customer loyalty among industrial customers of the public electricity utility organisation in Malawi using correlation and regression analyses.

A cross‐sectional survey was used with a sample of 92 respondents drawn from a population of 286 industrial customers of the public electricity utility in the Southern Region of Malawi. Data were collected using a pre‐tested questionnaire based on SERVQUAL and multi‐item scales to measure customer satisfaction and loyalty.

The findings suggest that the service quality is poor irrespective of demographic characteristics of the industrial customers. Furthermore, the findings show that the public electricity utility industrial customers are dissatisfied with the service offered and are disloyal to the public electricity utility. However, the level of loyalty is moderated by level of consumption. Large consumers are less disloyal than small consumers. Finally, the findings suggest that there is a strong relationship between service quality, customer satisfaction and customer loyalty among the public electricity utility's industrial customers and that the relationship between service quality and customer loyalty is partially mediated by customer satisfaction.

The study focused on functional quality offered by the public electricity utility to its industrial customers within Southern Region of Malawi limiting its generalisability. Additionally, it used the original SERVQUAL scale and some items may not be relevant to electricity utility organisation.

The paper has a significant diagnostic value in the sense that it identifies areas where the public electricity utility must direct its resources in order to satisfy its industrial customers.

The paper extends the examination of the relationship between service quality, customer satisfaction and customer loyalty into public sectors of a predominantly associative culture in developing countries. Specifically, it extends the research into electricity utility organisations that operates in a monopolistic market.

This paper aims to explore Turkey’s current energy status with a on renewable energy sources (RES) cooperation mechanisms, within the framework of RES Directive 2009/28/EC. The study uses the SWOT (strengths, weaknesses, opportunities, threats) analysis for drawing results about perspectives of RES cooperation between Turkey and European Union (EU) Member States. In particular, the SWOT analysis provides a clearer view of expanding RES in Turkey, as well as the level of utilization and potential of cooperation mechanisms and renewable energy in the country.

The approach followed incorporates desktop analysis, stakeholders’ mapping and involvement, key factors’ identification and results analysis and validation. The adopted approach is based on research conducted within the context of the “Bringing Europe and Third countries closer together through renewable Energies (BETTER)” (project number: IEE/11/845/SI2.616378) project, co-financed by the Intelligent Energy Europe Programme.

Based on the SWOT analysis conducted for Turkey, there are huge opportunities for RES deployment and cooperation in the country, because of its large unexploited RES potential. Turkey is a country with strategic importance, e.g. regarding energy security. Substantial savings can occur for the EU28 Member States through this cooperation, whereas Turkey will also benefit through income and investments, as well as technology transfers and further synergies associated with the cooperation. For the above potentials to be reached, nevertheless, national policies for RES development would have to be strengthened substantially, and non-economic barriers mitigated.

The potential of Turkey to utilise cooperation mechanisms provides opportunities for RES exporting between the country and EU countries. An analysis of these opportunities for cooperation will allow drawing clearer conclusions on cooperation potentials and business cases for Turkey.

The concept of knowledge cities (KCs) offers advantages to any urban region. Many cities globally claim themselves as being already KCs, while other cities have elaborated strategic plans in order to integrate this concept into their operational structures. The examination of their approaches reveals however that these initiatives are fragmented. The purpose of this paper is to present a multi‐dimensional and integrated decision support model for a KC's strategy formulation.

Reference is made to a methodological approach (KnowCis) for the integrated development of a KC, consisting of five main phases and taking into account nine different dimensions. The strategy formulation phase is a particularly complex procedure for any authority (e.g. local government or city's development agency). The reasons for this complexity are related to the amplitude of the KC concept, to the variety of the factors to be considered as well as to the challenge for balancing the needs and interests of different target groups.

The proposed model consists of the following building blocks: identification of the appropriate actions (based on the KnowCis methodology), modeling of the city's current status as a KC (via the development of related indicators), assessment of actions' necessity (based on the indicators' outcomes and through the benchmarking of other successful KCs cases), selection of the most appropriate form for each proposed action (based on their efficiency during the last reference period) and, finally, prioritisation of the proposed actions (based on a multi‐criteria approach).

The main suggestion for future research is the development of an intelligent information system which will incorporate the building blocks of the proposed model.

The originality and value of the paper is that the proposed model can be a really helpful decision support tool for any city which is developing a knowledge‐based strategy.

Managing large amounts of information and efficiently using this information in improved decision making has become increasingly challenging as businesses collect terabytes of data. Intelligent solutions, based on neural networks (NNs) and genetic algorithms (GAs), to solve complicated practical problems in various sectors are becoming more and more widespread nowadays. The current study provides an overview for the operations researcher of the neural networks and genetic algorithms methodology, as well as their historical and current use in business. The main aim is to present and focus on the wide range of business areas of NN and GA applications, avoiding an in‐depth analysis of all the applications – with varying success – recorded in the literature. This review reveals that, although still regarded as a novel methodology, NN and GA are shown to have matured to the point of offering real practical benefits in many of their applications.

The European Union (EU) energy supply environment is changing significantly and in a dynamic way, establishing the issue of safe energy imports as main priority. Greece relies heavily on energy imports. Furthermore, Greece aims to be elevated into an energy cross road for the energy supply to the EU. In this respect, the aim of this paper is the investigation of the suitability of graph theory concepts on energy supply networks and its application to represent energy corridors to Greece.

Supporting frameworks to represent and assess the vulnerability of the corridors satisfying the Greek demand in oil and gas are considered a crucial issue and are presented in this paper, based on the graph theory approach. In addition, a pilot application of the shortest path algorithm and the maximum flow at minimum risk algorithm for the oil and gas corridors to Greece is presented and discussed.

This paper introduces the application of graph theory to energy policy analysis. Indeed, the pilot application in oil and gas supply corridors to Greece, although quite simplified, has indicated the applicability of graph theory concepts in such problems and is considered a step forward of the existing studies, supporting the design efforts towards the development of a more reliable energy supply system.

To the best of the authors' knowledge, graph theory's application to energy corridors is not available in the international literature. In this respect, the added value of the paper is the provision of a sufficient decision support framework for the representation and assessment of the energy corridors' risk of energy availability, through the application of graph theory.