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What is Transformation Technique

Handbook of Research on Organizational Transformations through Big Data Analytics
Selects only one choice from a set of multi-choice for each coefficient of objective function and provides an optimal solution to the model.
Published in Chapter:
Solving Solid Transportation Problems with Multi-Choice Cost and Stochastic Supply and Demand
Sankar Kumar Roy (Vidyasagar University, India) and Deshabrata Roy Mahapatra (Vidyasagar University, India)
DOI: 10.4018/978-1-4666-7272-7.ch023
In this chapter, the authors propose a new approach to analyze the Solid Transportation Problem (STP). This new approach considers the multi-choice programming into the cost coefficients of objective function and stochastic programming, which is incorporated in three constraints, namely sources, destinations, and capacities constraints, followed by Cauchy's distribution for solid transportation problem. The multi-choice programming and stochastic programming are combined into a solid transportation problem, and this new problem is called Multi-Choice Stochastic Solid Transportation Problem (MCSSTP). The solution concepts behind the MCSSTP are based on a new transformation technique that will select an appropriate choice from a set of multi-choice, which optimize the objective function. The stochastic constraints of STP converts into deterministic constraints by stochastic programming approach. Finally, the authors construct a non-linear programming problem for MCSSTP, and by solving it, they derive an optimal solution of the specified problem. A realistic example on STP is considered to illustrate the methodology.
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