TY  - BOOK
SN  - 9781466620865
TI  - Hybrid linear search, genetic algorithms, and simulated annealing for fuzzy nonlinear industrial production planning problems
EP  - 109
SP  - 87
N2  - This chapter outlines an introduction to real-world industrial problem for product-mix selection involving eight variables and twenty one constraints with fuzzy technological coefficients, and thereafter, a formulation for an optimization approach to solve the problem. This problem occurs in production planning in which a decision maker plays a pivotal role in making decision under fuzzy environment. Decision-maker should be aware of his/her level of satisfaction as well as degree of fuzziness while making the product-mix decision. Thus, a thorough analysis is performed on a modified S-curve membership function for the fuzziness patterns and fuzzy sensitivity solution is found from the various optimization methodologies. An evolutionary algorithm is proposed to capture the optimal solutions respect to the vagueness factor and level of satisfaction. The near global optimal solution for objective function is obtained by hybrid meta-heuristics optimization algorithms such as line search, genetic algorithms, and simulated annealing. © 2013, IGI Global.
A1  - Vasant, P.
Y1  - 2012///
N1  - cited By 11
AV  - none
ID  - scholars2396
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84900610080&doi=10.4018%2f978-1-4666-2086-5.ch003&partnerID=40&md5=07f0bbf9814adb3f5b8f421056c20694
PB  - IGI Global
ER  -