Informatics Publishing Limited

Anita Biswas ¹, Smita Verma ²

Affiliations
1 Truba College of Technology, Indore, IN
2 S.G.S. Institute of Technology & Science, Indore, IN

Abstract

In this paper an attempt is made to explain the basic concept of efficiency, frontier production function, technical efficiency, deterministic frontier, and stochastic frontier. Efficiency of a firm/industry refers to its performance in the utilization of resources at its disposal and is a relative concept. Technical efficiency of a production function is defined as the maximum quantity of output obtainable from given set of inputs. A failure to produce the greatest possible output means the technical decision is in efficient. Technical inefficiency can be obtained by the methods stochastic and deterministic production frontier models. The method discussed in this paper has several possible extension and generalization. Technical efficiency has many policy implications in various functional areas of modern management.

Keywords

Production Function, Frontier, Efficiency, Technical Efficiency.

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Smita Verma ¹, Anita Biswas ²

Affiliations
1 S.G.S. Institute of Technology & Science, Indore, IN
2 Truba College of Technology, Indore, IN

Abstract

There has been an ever growing concern to measure efficiency of decision making units (DMUs). Parametric approaches have been the popular methods for measuring the same. Data Envelope Analysis (DEA) is an addition in this domain. This paper is an attempt to understand the concept of DEA approach. DEA is a Linear Programming Problem that provides a means of calculating apparent efficiency levels within a group of organizations. The efficiency of an organization is calculated relative to the group's observed best practice. In other words, we may say that, DEA is essentially an optimization algorithm, which develops efficiency scores for all DMUs on a scale from zero to hundred percent.

Keywords

Production Function, Frontier, Technical Efficiency, DEA, DMU.

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Smita Verma ¹, Megha Jain ¹, Ranjana Singh ¹

Affiliations
1 Department of Applied Mathematics & Computational Science, S.G.S. Institute of Technology & Science, 23-Park Road, Indore-452003 (M.P.), IN

Abstract

In sequencing problems, there are one or more jobs to be done and one or more machines are available for this purpose. If at least one machine center includes more than one machine, the scheduling problem becomes a flexible flow-shop problem. Flexible flow shops are thus generalization of simple flow shops. In this paper, we are solving flexible flow shop sequencing problem of two machine centers, using an algorithm. The proposed algorithm will be suitable for a medium-sized number of jobs;it is an optimal algorithm, entirely using the search-and-prune technique.

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