A Multiobjective Multi-Item Inventory Control Problem in Fuzzy-Rough Environment Using Soft Computing Techniques
The optimal production and advertising policies for an inventory control system of multi-item multiobjective problem under a single management are formulated as an optimal control problem with resource constraints under inflation and discounting in fuzzy rough (Fu-Ro) environment. The objectives and...
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doaj-73a1a84638d54d889c55c31fe0a4e3422020-11-25T00:20:24ZengAsia UniversityAdvances in Decision Sciences2090-33592090-33672014-01-01201410.1155/2014/617989617989A Multiobjective Multi-Item Inventory Control Problem in Fuzzy-Rough Environment Using Soft Computing TechniquesDipak Kumar Jana0K. Maity1M. Maiti2T. K. Roy3Department of Engineering Science, Haldia Institute of Technology, Haldia, West Bengal 721657, IndiaDepartment of Mathematics, Mugberia Gangadhar Mahavidyalaya, Mugberia, Purba Medinipur, West Bengal 721425, IndiaDepartment of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Medinipur, West Bengal 721 102, IndiaDepartment of Mathematics, Bengal Engineering and Science University, Shibpur, Howrah, West Bengal 711103, IndiaThe optimal production and advertising policies for an inventory control system of multi-item multiobjective problem under a single management are formulated as an optimal control problem with resource constraints under inflation and discounting in fuzzy rough (Fu-Ro) environment. The objectives and constraints in Fu-Ro are made deterministic using fuzzy rough expected values method (EVM). Here, the production and advertisement rates are unknown and considered as control (decision) variables. The production, advertisement, and demand rates are functions of time t. Maximization of the total proceed from perfect and imperfect units and minimization of the total cost consisting of production, holding, and advertisement costs are formulated as optimal control problems and solved directly using multiobjective genetic algorithm (MOGA). In another method for solution, membership functions of the objectives are derived and the multi-objective problems are transformed to a single objective by the convex combination of the membership functions and then the problem is solved by generalized reduced gradient (GRG) method. Finally, numerical experiment and graphical representation are provided to illustrate the system.http://dx.doi.org/10.1155/2014/617989 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dipak Kumar Jana K. Maity M. Maiti T. K. Roy |
spellingShingle |
Dipak Kumar Jana K. Maity M. Maiti T. K. Roy A Multiobjective Multi-Item Inventory Control Problem in Fuzzy-Rough Environment Using Soft Computing Techniques Advances in Decision Sciences |
author_facet |
Dipak Kumar Jana K. Maity M. Maiti T. K. Roy |
author_sort |
Dipak Kumar Jana |
title |
A Multiobjective Multi-Item Inventory Control Problem in Fuzzy-Rough Environment Using Soft Computing Techniques |
title_short |
A Multiobjective Multi-Item Inventory Control Problem in Fuzzy-Rough Environment Using Soft Computing Techniques |
title_full |
A Multiobjective Multi-Item Inventory Control Problem in Fuzzy-Rough Environment Using Soft Computing Techniques |
title_fullStr |
A Multiobjective Multi-Item Inventory Control Problem in Fuzzy-Rough Environment Using Soft Computing Techniques |
title_full_unstemmed |
A Multiobjective Multi-Item Inventory Control Problem in Fuzzy-Rough Environment Using Soft Computing Techniques |
title_sort |
multiobjective multi-item inventory control problem in fuzzy-rough environment using soft computing techniques |
publisher |
Asia University |
series |
Advances in Decision Sciences |
issn |
2090-3359 2090-3367 |
publishDate |
2014-01-01 |
description |
The optimal production and advertising policies for an inventory control system of multi-item
multiobjective problem under a single management are formulated as an optimal control problem with resource
constraints under inflation and discounting in fuzzy rough (Fu-Ro) environment. The objectives
and constraints in Fu-Ro are made deterministic using fuzzy rough expected values method (EVM). Here,
the production and advertisement rates are unknown and considered as control (decision) variables. The
production, advertisement, and demand rates are functions of time t. Maximization of the total proceed from
perfect and imperfect units and minimization of the total cost consisting of production, holding, and advertisement
costs are formulated as optimal control problems and solved directly using multiobjective genetic
algorithm (MOGA). In another method for solution, membership functions of the objectives are derived and
the multi-objective problems are transformed to a single objective by the convex combination of the membership
functions and then the problem is solved by generalized reduced gradient (GRG) method. Finally, numerical experiment
and graphical representation are provided to illustrate the system. |
url |
http://dx.doi.org/10.1155/2014/617989 |
work_keys_str_mv |
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