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Showing 2 results for Kaviani
Mehdi Abbasi, Mohamad Amin Kaviani,
Volume 1, Issue 3 (11-2014)
Abstract
In competitive markets, the operations strategies of companies are normally formulated based on their competitive advantages. An effective operations strategy should maintain and improve competitive advantages based on the capabilities of the corporate operations resources. Considering the market requirements and the operational performance of the rivals is the key for success and survival of a company in the competition. Therefore, recognizing where a company stands in comparison with its rivals and adopting the appropriate operations strategy plays vital roles in the success of companies. This paper proposes a method for comparing and ranking operations strategies of companies based on the concept of efficient frontier using data envelopment analysis (DEA) in grey environment. In the aforementioned method, DEA is used to evaluate the efficiency of operations strategies of manufacturing firms. Also, grey theory is used to support the uncertainty of the experts’ opinions regarding the inputs and outputs of the DEA model. Then the respective units are ranked, and analyses are performed. The proposed approach is applied for the entire nine cement factories of Fars Province in Iran, and the units are ranked, respective analyses are presented regarding the efficient and inefficient units.
Mehdi Alinaghian, Zahra Kaviani, Siyavash Khaledan,
Volume 2, Issue 2 (8-2015)
Abstract
A significant portion of Gross Domestic Production (GDP) in any country belongs to the transportation system. Transportation equipment, in the other hand, is supposed to be great consumer of oil products. Many attempts have been assigned to the vehicles to cut down Greenhouse Gas (GHG). In this paper a novel heuristic algorithm based on Clark and Wright Algorithm called Green Clark and Wright (GCW) for Vehicle Routing Problem regarding to fuel consumption is presented. The objective function is fuel consumption, drivers, and the usage of vehicles. Being compared to exact methods solutions for small-sized problems and to Differential Evolution (DE) algorithm solutions for large-scaled problems, the results show efficient performance of the proposed GCW algorithm.
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