Assessing competitiveness of foreign and local supermarket chains in Vietnamese market by using Fuzzy TOPSIS method

Considering the strategic importance for supermarket chains and to understanding the critical elements affecting their competitiveness and their relative level of competitiveness, this study tries to assess competitiveness of foreign and local supermarket chains in Vietnam using the fuzzy TOPSIS method. The results show that, even smaller size Vietnamese supermarket chains, when compared to foreign chains, are still slightly higher in competitiveness.Competitiveness; Supermarket chains; Fuzzy TOPSIS

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Risk assessment of blasting operations in open pit mines using FAHP method

Purpose. In the mining blasting operation, fragmentation is the most important output. Fly rock, ground vibration, air blast, and environmental effects are detrimental effects of blasting operations. Identifying and ranking the risk of blasting operations is considered as the most important stage in project management. Methods. In this research, the problem of identifying and ranking the factors constituting the risk in blasting operations is considered with the methodology of the Fuzzy Analytical Hierarchy Process (FAHP). Criteria and sub-criteria have been determined based on historical research studies, field studies, and expert opinions for designing a hierarchical process. Findings. Based on FAHP scores, non-control of the sub-criterion of health and safety (C3), blast operation results (C18) and knowledge, and skill and staffing (C2) with a score of 0.377, 0.334, and 0.294 respectively are the most effective sub-criterion for the creation of blasting operations risk. According to the score, the sub-criterion C18 is the most effective sub-criterion in providing the blasting operations risk. Effects and results of blasting operations (D8), with a score of 0.334 as the most effective criterion, and natural hazards (D10), with a score of 0.015, were the last priorities in the factors causing blasting operations risk. Originality. Regarding the risk rating of blasting operations, the control of the sub-criteria C3, C18, and C2, and the D8 criterion, is of particular importance in reducing the risk of blasting operations and improving project management. Practical implications. The evaluation of human resource performance and increase in the level of knowledge and skills and occupational safety and control of all outputs of blasting operations is necessary. Therefore, selecting the most important project risks and taking actions to remove them is essential for risk management.Мета. Визначення ризиків проведення вибухових робіт та їх оцінка на основі використанням нечіткого методу аналізу ієрархій (НМАІ) для покращення управління якістю проектів. Методика. В рамках даного дослідження, проблеми визначення та оцінки ризиків вибухових робіт розглядалися із застосуванням нечіткого методу аналізу ієрархій. На базі аналізу історичних даних і польового дослідження з урахуванням експертних оцінок були визначені критерії та підкритерії для побудови ієрархій. Результати. За результатами НМАІ, неконтролюючий підкритерій здоров’я та безпеки (С3), підкритерій результатів вибухових робіт (С18), знань, умінь і кадрів (С2) зі значеннями 0.377, 0.334 і 0.294 відповідно найбільш ефективні в появі ризику проведення вибухових робіт. Підкритерій С18 чинить найбільший вплив на ризик проведення вибухових робіт. Критерій результатів і наслідків вибухових робіт (D8) з найефективнішим значенням 0.334 та критерій природних катастроф (D10) зі значенням 0.015 є останніми пріоритетами серед чинників, які визначають ризик проведення вибухових робіт. Наукова новизна. Отримав доповнення та подальший розвиток науково-методичний підхід до визначення ризиків при проведенні вибухових робіт, заснований на їх ранжуванні з використанням системи виявлених критеріїв і підкритеріїв методом НМАІ. Практична значимість. Для успішного керування проектом важливо визначати найсерйозніші ризики проекту й вжити заходів щодо їх усунення. Відносно ранжирування ризиків проведення вибухових робіт управління підкритеріями C3, C18 і C2, а також критерієм D8, особливо важливо для зниження цих ризиків та покращення якості управління проектом.Цель. Определение рисков проведения взрывных работ и их оценка на основе использования нечеткого метода анализа иерархий (НМАИ) для улучшения управления качеством проектов. Методика. В рамках данного исследования, проблемы определения и оценки рисков взрывных работ рассматривались с применением нечеткого метода анализа иерархий. На базе анализа исторических данных и полевого исследования с учетом экспертных оценок были определены, критерии и подкритерии для построения иерархий. Результаты. По результатам НМАИ, неконтролирующий подкритерий здоровья и безопасности (С3), подкритерий результатов взрывных работ (С18), знаний, умений и кадров (С2) со значениями 0.377, 0.334 и 0.294 соответственно наиболее эффективны в появлении риска проведения взрывных работ. Подкритерий С18 оказывает самое большое влияние на риск проведения взрывных работ. Критерий результатов и последствий взрывных работ (D8) с самым эффективным значением 0.334 и критерий природных катастроф (D10) со значением 0.015 являются последними приоритетами среди факторов, которые определяют риск проведения взрывных работ. Научная новизна. Получил дополнение и дальнейшее развитие научно-методический подход к определению рисков при проведении взрывных работ, основанный на их ранжировании с использованием системы выявленных критериев и подкритериев методом НМАИ. Практическая значимость. Для успешного руководства проектом важно определять самые серьезные риски проекта и предпринять действия по их устранению. В отношении ранжирования рисков проведения взрывных работ управление подкритериями C3, C18 и C2, а также критерием D8, особенно важно для снижения этих рисков и улучшения руководства проектом.The authors would like to thank Mining Engineering Department, Islamic Azad University (South Tehran Branch) for supporting this research

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment