Partical Swarm Optimization in Job Shop Scheduling and Designing the Layout for the Industry

In this paper particle swarm optimization algorithm has been used for job shop scheduling problem. Job shop scheduling is a combinatorial optimization problem where we have to arrange the jobs which may or may not be processed in every machine in a particular sequence and each machine has a different sequence of jobs. Job shop scheduling is a complex extended version of flow shop scheduling which is a problem where each job is processed through each and every machine and each machine has a same sequence of jobs. PSO (Particle swarm optimization) helps us to find a combination of job sequence which has the least make span. In PSO a swarm of particles which have definite position and velocity for each job. In PSO, to find the combinations we use a heuristic rule called Smallest Position Value (SPV). According to smallest position value rule jobs are arranged in ascending order of their positions i.e. job having least position value is put first in sequence. In previous research, PSO particles search solutions in a continuous solution space. Since the solution space of the JSP is discrete, the particle position representation has been modified for particle movement, and particle velocity to better suit PSO for the JSP. Single Row Facility Layout Problem (SRFLP) consists of arranging a number of rectangular facilities with varying length on one side of a straight line to minimize the weighted sum of the distance between all facility pairs. In this paper Particle Swarm Optimization (PSO) algorithm has been used to solve the SRFLP.