A Nature Inspired Firefly Heuristic Approach On Optimization Of Multi Objective Job Shop Scheduling Problems
Due to rapid increase in modernization and globalization in today’s economy, every manufacturing industry faces
great challenges to minimize their manufacturing cost and to sustain in the competitive market. Scheduling is the earmarking
of resources over time to effectuate an agglomeration of tasks ordained in any field of engineering and non engineering. Job
shop scheduling problem is the most labyrinthine and paradigmatic problem of all kinds of production scheduling problems.
Preponderance of JSSP is buttoned down into non deterministic (NP) hard problem because of its complexity and
entanglement. Scheduling are generally elucidated by using heuristics to obtain optimal or near optimal solutions because
problems found in practical applications cannot be fathomed to optimality using available resources in many cases. Many
researchers attempted to iron out the problem by applying various optimization techniques. While using traditional methods
they observed huge impasse in deciphering high complex problems and meta-heuristic algorithms were proved most
efficacious algorithms to solve various JSSP so far. The objective of this paper i) to bestow a newly developed meta heuristic
called Firefly algorithm (FA) because of inspiration on Firefly and its characteristic. ii) To treasure out the combined objective
function by determining optimal make span, mean flow time and tardiness of different size problems using two Bagchi Job
Shop Scheduling Problems ( JSP-1 and JSP – 2) and iii) to prove that the proposed FFA algorithm is a gratifying problem
solving technique for JSSP with multi criteria.