Although supply chains disruptions rarely occur, their negative effects are prolonged and severe. In this paper, we propose a reliable capacitated supply chain network design (RSCND) model by considering random disruptions in both distribution centers and suppliers. The proposed model determines the optimal location of distribution centers (DC) with the highest reliability, the best plan to assign customers to opened DCs and assigns opened DCs to suitable suppliers with lowest transportation cost. In this study, random disruption occurs at the location, capacity of the distribution centers (DCs) and suppliers. It is assumed that a disrupted DC and a disrupted supplier may lose a portion of their capacities, and the rest of the disrupted DC & apos; s demand can be supplied by other DCs. In addition, we consider shortage in DCs, which can occur in either normal or disruption conditions and DCs, can support each other in such circumstances. Unlike other studies in the extent of literature, we use new approach to model the reliability of DCs; we consider a range of reliability instead of using binary variables. In order to solve the proposed model for real-world instances, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied. Preliminary results of testing the proposed model of this paper on several problems with different sizes provide seem to be promising.

These days, we see many organizations with extremely complex systems with various processes, organizational units, individuals, and information technology support where there are complex relationships among their various elements. In these organizations, poor architecture reduces efficiency and flexibility. Enterprise architecture, with full description of the functions of information technology in the organization, attempts to reduce the complexity of the most efficient tools to reach organizational objectives. Enterprise architecture can better assess the optimal conditions for achieving organizational goals. For evaluating enterprise architecture, executable model need to be applied. Executable model using a static architectural view to describe necessary documents need to be created. Therefore, to make an executable model, we need a requirement to produce products of the enterprise architecture to create an executable model. In this paper, for the production of an enterprise architecture, object-oriented approach is implemented. We present an algorithm to use stereotypes by considering reliability assessment. The approach taken in this algorithm is to improve the reliability by considering additional components in parallel and using redundancy techniques to maintain the minimum number of components. Furthermore, we implement the proposed algorithm on a case study and the results are compared with previous algorithms.

The human error has been reported as a major root cause in road accidents in today’s world. The human as a driver in road vehicles composed of human, mechanical and electrical components is constantly exposed to changing surroundings (e.g., road conditions, environment)which deteriorate the driver’s capacities leading to a potential accident. The auto industries and transportation authorities have realized that similar to other complex and safety sensitive transportation systems, the road vehicles need to rely on both advanced technologies (i.e., Advanced Driver Assistance Systems (ADAS)) and Passive Safety Systems (PSS) (e.g.,, seatbelts, airbags) in order to mitigate the risk of accidents and casualties. In this study, the advantages and disadvantages of ADAS as active safety systems as well as passive safety systems in road vehicles have been discussed. Also, this study proposes models that analyze the interactions between human as a driver and ADAS Warning and Crash Avoidance Systems and PSS in the design of vehicles. Thereafter, the mathematical models have been developed to make reliability prediction at any given time on the road transportation for vehicles equipped with ADAS and PSS. Finally, the implications of this study in the improvement of vehicle designs and prevention of casualties are discussed.

One of the primary concerns on supply chain management is to handle risk components, properly. There are various reasons for having risk in supply chain such as natural disasters, unexpected incidents, etc. When a series of facilities are built and deployed, one or a number of them could probably fail at any time due to bad weather conditions, labor strikes, economic crises, sabotage or terrorist attacks and changes in ownership of the system. The objective of risk management is to reduce the effects of different domains to an acceptable level. To overcome the risk, we propose a reliable capacitated supply chain network design (RSCND) model by considering random disruptions risk in both distribution centers and suppliers. The proposed study of this paper considers three objective functions and the implementation is verified using some instance.

Traditional assembly lines are still attractive means of mass and large-scale series production. Previous research works mainly dealt with the minimization of balancing loss, subject to precedence constraints. Very recently the focus of attention shifted towards system loss. However, these losses are not the proper indicators of the stability of the system since the efficiency of the assembly line increases normally when the stability of the system increases. In this paper, we introduce a new type of assembly line, which is totally different form the existing types of assembly line studied in the literature. In this work, we define the stability of the system in terms of reliability of the assembly line. The objective is to design an assembly line with a desired level of working stability measured through this reliability measure. This special type of assembly line, where production rate can be increased by minimizing the cycle time subject to a given level of reliability and precedence constraints, extends the decision-making framework available in the literature on assembly line balancing problem and indirectly takes care of both balancing loss and system loss.