Global supply chains have to manage production over the whole world. Therefore, production plants are needed to supply the demand of products and parts. Due to complication and uncertainty of production market, portfolio selection is one of the most challenging problems. Type-2(T2) fuzzy is a model, which provides the ability to handle the effect of uncertainty. Aiming at this problem, we propose a T2 supplier management system operation scheme, which not only employs fuzzy C-Means clustering algorithm by dynamically increasing cluster center, but also it achieves good classification performance. The key result is that fuzzy classification applications improve the planning and operating of supply and demand in a distributed production and global supply chain.

In this paper, a multi products single machine economic production quantity model with
discrete delivery is developed. A unique cycle length is considered for all produced items with
an assumption that all products are manufactured on a single machine with a limited capacity.
The proposed model considers different items such as production, setup, holding, and
transportation costs. The resulted model is formulated as a mixed integer nonlinear
programming model. Harmony search algorithm, extended cutting plane and particle swarm
optimization methods are used to solve the proposed model. Two numerical examples are used
to analyze and to evaluate the performance of the proposed model.

This paper proposes the social network analysis (SNA), to study interaction among various
activities in a product development process (PDP). The implementation of SNA helps to
measure the properties of information flow and identifies PDP activities and limitations. The
findings of an exploratory research project which explores the potential of SNA, as an improve
tool for visually mapping and analyzing the stakeholders relationships found across the IC
substrates design/manufacturing’s PDP of the Unimicron Technology Corp. From the findings,
the authors prescribe the necessary SNA recommendations to improve the social conditions
within the PDP.

This paper proposes a particle swarm optimization (PSO) algorithm to solve various types of economic dispatch (ED) problems in power systems such as, environmental/economic dispatch (EED) and multi-area environmental/economic dispatch. The proposed model considers the environmental impact to achieve the minimization of fuel costs and pollutant emissions, simultaneously. The EED problem is further extended to dispatch the power among different areas to aid emission allowance trading. The performance of the proposed PSO is compared with conventional method and genetic algorithm. The results clearly show that the proposed algorithms give global optimum solution compared to the other methods. The results obtained also show that the proposed PSO algorithms can provide comparable dispatch solutions with reduced computation time for all types of ED problems.

An efficient and practical, three-component one-pot condensation reaction between 1, 2-phenylenediamine, 2-mercaptoacetic acid and aromatic aldehydes in ionic liquids have been reported for the synthesis of 1-aryl-1H, 3H-thiazolo [3, 4-a] benzimidazoles derivatives in excellent yields.