Informatics Publishing Limited

G. N. Chaithra ¹, B. Tambat ², N. S. Prasanna ³, C. Srinivas ¹

Affiliations
1 Department of Biotechnology and Microbiology, Bangalore University, Bangalore., IN
2 Department of Crop Physiology, Uas-b, Agricultural College Campus, Hassan, Karnataka., IN
3 Department of Biotechnology, Uas-d, Krishi Nagar, Dharwad, Karnataka., IN

Abstract

Midimaavu is one of the mango varieties known for making pickles. Unlike mango slices, entire tender mango is used for pickling and the pickles can be stored up to 3 to 4 years without any preservatives. However, it has been reported that most Midimaavu varieties are restricted to certain geographical locations in central Western Ghats, India and are harvested mostly from the forests. Thus they are considered as an important non-timber forest produce (NTFP) in the areas. We assessed the demographic profile of Midimaavu in Chikmagalur district, central Western Ghats, Karnataka. As per results, the typical reverse "J" shaped curve was not observed in many populations. Further the density and regeneration per adult analysis indicated populations suffer due to poor regeneration and subsequent sapling survival. The present study reveals that midimaavu is suffering from low recruitment and survival, thus there is an urgent need for conservation action.

Keywords

Midimaavu, Demography, Conservation, Central Western Ghats.

Full Text

     

C. Srinivas ¹, K. Ramji ², B. Satyanarayana ², Naveen Ravela ³

Affiliations
1 Department of Mechanical Engineering, RVR & JC College of Engineering, Guntur-522019, Andhra Pradesh, IN
2 Department of Mechanical Engineering, Andhra University, Visakhapatnam- 530003, Andhra Pradesh, IN
3 SCR Engineering College, Guntur-522619, Andhra Pradesh, IN

Abstract

The layout of a Flexible Manufacturing System (FMS) involves distributing different resources in the given FMS and achieving maximum efficiency of the services offered. With this in mind FMSs are designed to optimize production flow from the first stages as raw material to the finished product. Layout problems are known to be complex and are generally NP (non polynomial) hard. The problems of NP are not easily solvable within the deterministic time. The arrangement of workstations determines how long the materials have to travel and the associated material handling cost. Various heuristics and metaheuristics are used to solve NP hard problems. Out of these Genetic Algorithm (GA) and Ant Colony Optimization (ACO) are found to be effective metaheuristics to solve layout problems. Since the metaheuristics give a near optimal solution but not an accurate solution, for a large solution space, a single heuristic solution may not be appropriate especially when the number of workstations is large. Hence it is always important to obtain a solution for a layout problem by more than one technique like Genetic Algorithm, Ant Colony Algorithm. The objective of the present study is to find out the optimum FMS layout which yields minimum total transportation cost, by using Genetic Algorithm (GA) and Ant Colony Optimisation (ACO).

Keywords

Layout Design, Flexible Manufacturing Systems, Genetic Algorithm, Ant Colony Optimisation.

Full Text

   

T. V. S. R. K. Prasad ¹, Kolla Srinivas ², C. Srinivas ²

Affiliations
1 Dept of Automobile Engg., Eswar College of Engg, Kesanupalli, Narasaraopeta, Guntur District, Andhra Pradesh, IN
2 Dept of Mechanical Engg, R. V. R & J. C. College of Engg., Chowdavaram, Guntur District, Andhra Pradesh, IN

Abstract

Most companies nowadays are organized into networks of manufacturing and distribution sites that procure raw materials, process them into finished goods, and distribute the finished goods to customers. The goal is to deliver the right product to the right place at the right time for the right price. This production - distribution network is what we call "supply chains. After years of focusing on reduction in manufacturing and operating costs , companies are beginning to look into transportation costs to further reduce the costs. In the present paper an integrated view of the supply chain has been proposed. The proposed model takes into consideration the manufacturing, inventory and distribution costs involved in a supply chain consisting of multiple plants, multiple warehouses producing different products and supplying to different customers with different demands for the finished product. The proposed model is formulated to minimise the total cost of the supply chain.

Keywords

Supply Chain Management, Integrated SCM, Inventory.

Full Text

     

T. V. S. R. K. Prasad ¹, Kolla Srinivas ², C. Srinivas ²

Affiliations
1 Department of Mechanical Engineering, Kallam Haranadha Reddy Institute of Technology, Chowdavaram, Guntur, Andhra Pradesh, IN
2 Mechanical Engineering Department, R.V.R & J.C. College of Engineering, Chowdavaram, Guntur, Andhra Pradesh, IN

Abstract

Inventory management is very important area in the supply chain management. Excess stocks may lead to incurring holding costs while shortage of stocks lead to shortage costs. The problem becomes more complicated when several factories produce multiple products in multiple time periods and supplies to several distribution centers who in turn supply to various agents and customers. With the advances in information technology and computing methods the inventory management problem in a multi echelon supply chain can be solved reasonably well. This paper presents an approach for the multi product inventory optimization in a multi echelon supply chain using Artificial Bee Colony Optimization method.

Keywords

Multi Product Inventory, Supply Chain, Artificial Bee Colony Optimization.

Full Text