This paper proposes a novel genetic algorithm (GA) approach that utilizes multichromosome to solve the flexible job-shop scheduling problem (FJSP), which involves two kinds of decisions: machine selection and operation sequencing. Typically, former is represented by string categorical values, whereas latter forms sequence operations. Consequently, chromosome conventional GAs for solving FJSP co...

Genetic algorithms are a very popular heuristic which have been successfully applied to many optimization problems within the last 30 years. In this chapter, we give a survey on some genetic algorithms for shop scheduling problems. In a shop scheduling problem, a set of jobs has to be processed on a set of machines such that a specific optimization criterion is satisfied. According to the restr...

This paper studies the single hoist scheduling problem in no-wait flexible flow shop system with constant process times. The objective is to minimize the make span in the given job tasks. Different jobs have different process routes and process times. When a job starts, workstation must be free to process the job, and as soon as it is finished, the hoist must be free to move it to the next work...

This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for t...

The various industries such as automobile industry, aerospace industry, printing industry, and chemical industry operate on job shop system. Job shop scheduling problems are complex and real world. The present work assesses the effect of change in shop utilizations levels on total setups and mean setup time measures. The simulation model of the job shop is developed for investigation purpose. T...