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Component-Based Software Engineering (CBSE) is an approach to building and developing software systems based on software components. In component-based software systems, there are various software components, including Commercial off the Shelf (COTS) and in-house components. Software developers can build their desired software component as in-house or COTS. The problem of deciding optimally between COTS and in-house components is one of the major challenges of software developers, which is known as the component selection problem. This can be resolved by evaluating the criteria for optimality in component selection and then solving the component selection problem by optimization techniques. In this paper, an attempt was made to optimize the component selection problem through the multi-objective optimization by maximizing the Fuzzy-Intra Coupling Density (Fuzzy-ICD) and functionality as objective functions, and also taking into account budget, delivery time, reliability, and Fuzzy-ICD as constraints of multi-objective problems. Fuzzy ICD is a more accurate criterion to calculate the relationship between Cohesion and Coupling of components, which is obtained through the fuzzy computing of each of them, based on the Meyers classification. Thus, after a two-criterion optimization model formulation, this optimization problem was solved by fuzzy multi objectives approach. Finally, the proposed method was evaluated by performing the case study of financial-accounting system. Comparison of the results showed that the proposed method could select optimal components with maximum functionality and Fuzzy-ICD and fewer rates of time and Budget (0.29, 0.43, 1.1 s, and 88$ were the improved rates of functionality, Fuzzy-ICD, time, and budget, respectively).

One of the major issues in current oil sands waste management is the lack of a direct link between long-term mine plans and the quantity of the tailings produced downstream. This research is focused on developing a link between the oil sands' long-term mine plans and the final composite tailings (CT) produced downstream. The objective is to assist in making the oil sands production process comply with the regulations set by the Alberta Energy Resources and Conservation Board (Directive 074). A series of mass-balance relations between the ore tonnage and the final CT tonnage was developed. This was followed by implementing the mass-balance relations with a case study and reporting the CT production schedule from the long-term mine plan. To capture the uncertainties associated with the CT production process, a stochastic simulation model was developed. Finally, sensitivity analysis was carried out to capture the sensitivity of the CT tonnages produced to the fluctuations of the stochastic input variables. The link between the long-term mine schedule and tailings management plan helps mine planners to set a dyke construction schedule and raise the dyke height in each period in accordance with the volume of tailings produced. This research illustrates the uncertainties associated with the amount of CT produced over the mine life. Understanding these uncertainties will lead to improved and sustainable mining and waste management practices in oil sands mining industry.

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