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Minimization of Makespan and Total Tardiness in a Flow Shop Scheduling Using Artificial Neural Network
--Ashwani Kumar Dhingra, Naveen Kumar and Sunita Dhingra
The paper makes an attempt to minimize the makespan and total tardiness in the flow shop scheduling using Artificial Neural Network (ANN). A feed forward back propagation neural network is implemented for the optimal solution of the problem. The network has been trained with the optimal sequences for different jobs on five machines problem. The trained network is further considered for solving the problem of flow shop scheduling. The analysis of all the algorithms that are implemented is carried out using Nawaz, Enscore and Ham (NEH) heuristic for 5 to 10 jobs with 5 machines under Sequence Dependent Set-up Time (SDST) environment with due dates and weights allotted to each job. With the help of NEH heuristic, different sequences have been generated for the considered problem. The number of sequences obtained is assembled in 270 × 10 matrix for the input of neural network. The network is trained with Baygon regression training algorithm and finally the results obtained from the neural network are found to be 93% accurate.
© 2017 IUP. All Rights Reserved.
Investigating the Technical
and Scale Efficiencies of Indian
Textile Industry: A Target Setting
Based Analysis Through DEA
--Jatin Goyal, Harpreet Kaur and Arun Aggarwal
This paper attempts to measure the overall technical, pure technical and scale efficiencies in the Indian textile industry and provides target setting analysis for the same using cross-sectional data of 101 companies for the year 2014-15. For the purpose of analysis, we used a non-parametric linear programming technique named Data Envelopment Analysis (DEA) conceptualizing two outputs and five inputs technology. The empirical results showed that the level of Overall Technical Inefficiency (OTIE) in Indian textile industry is to the tune of about 16.44%, and out of this 11.79% points are principally attributed to managerial inefficiency rather than inappropriate choice of the scale size. The study underlines the need for concrete steps on the part of policy makers to withstand successfully the pressure of foreign competition by eliminating the managerial inefficiencies in the process of resource utilization and correcting the scale of operations through concerted efforts of technology infusion.
© 2017 IUP. All Rights Reserved.
Some Aspects of the Barrier Probability in a Classical Risk Model
--Palash Ranjan Das and Tripti Chakrabarti
In this paper, we have considered a classical risk model with dividend barrier, in which claim inter-occurrence times are exponentially distributed. Our aim is to obtain explicit expression for the barrier probability B(u, b), the upper barrier being assumed to be ‘b’, before ruin occurs when the claim amount distribution is either exponential or erlangian. It is to be noted that the premium loading factor is taken to be 20% in both the cases. In order to ensure fair comparison, we have chosen the exponential and erlangian parameters in such a way that their mean and hence the expected total claims are same for both the distributions over a given time interval. Ultimately, through numerical evaluation of the barrier probability for both the claim amount distributions, we investigate whether there is any significant difference between the two.
© 2017 IUP. All Rights Reserved.
Ranking of JIT Attributes
for Indian Manufacturing Industries Using TOPSIS Technique
--Amit Gupta
To sustain in a global competitive market, any organization needs to focus on quality products at viable prices. There is a huge stress on the industry to redesign supply chain. Just In Time (JIT) production system plays a vital role in prolonged sustainability of any organization. The objective of this paper is to evaluate and rank JIT attributes for Indian manufacturing industries. Tewari et al. (2016) have ranked the performance indicators in JIT-based production system for manufacturing industries using Simple Additive Weighting (SAW). In this paper, a new deterministic quantitative model based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been applied for this type of ranking problem. The paper shows that ranking of JIT attributes for Indian manufacturing industries is similar using SAW and TOPSIS techniques.
© 2017 IUP. All Rights Reserved.
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