A recent adaptive algorithm, named Ant System, is introduced and used to solve the problem of job shop scheduling. The algorithm was first introduced by Dorigo, Maniezzo and Colorni in 1991 and is derived from the foraging and recruiting behaviour observed in an ant colony. It can be applied to combinatorial optimisation problems. This paper outlines the algorithm’s implementation and performan...

The job shop scheduling problem is a combinatorial optimization problem and one of the most complex problems among various production scheduling problems. The present work assesses the effect of change in setup time’s levels on mean flow time and means tardiness measures. The simulation model of the job shop is developed for investigation purpose. Three levels of setup times i.e. SUL_1, SUL_2 a...

Many real-world scheduling problems are solved to obtain optimal solutions in term of processing time, cost and quality as optimization objectives. Currently, energy-efficiency is also taking into consideration in these problems. However, this problem is NP-Hard, so many search techniques are not able to obtain a solution in a reasonable time. In this paper, a genetic algorithm is developed to ...

We present a decomposition heuristic for a large class of job shop scheduling problems. This heuristic utilizes information from the linear programming formulation of the associated optimal timing problem to solve subproblems, can be used for any objective function whose associated optimal timing problem can be expressed as a linear program (LP), and is particularly effective for objectives tha...

A two level branch and bound algorithm is developed to solve an altered form of the standard flow-shop scheduling problem modeled as a bilevel programming problem. The flow-shop scheduling problem considered here differs from the standard problem in that operators are assigned to the machines and each operator has a different time table for the jobs on each machine. The shop owner is considered...

In simple flow shop problems, each machine operation center includes just one machine. If at least one machine center includes more than one machine, the scheduling problem becomes a flexible flow-shop problem. Recently, group scheduling has also been proposed and discussed. In the group scheduling, each job belongs to a specific group and all the jobs are processed group by group. In this pape...

The Job-Shop Scheduling (JSS) can be defined as a planning of schedules with many variations according to the requirements. In Job-Shop Scheduling Problem (JSSP) environment, there are numbers jobs to be processed on numbers of machines with a certain objective function to be minimized or maximized. In this paper, we have used the GT-GA to solve the job shop scheduling to minimize the makespan ...

Job-shop scheduling problem (JSP) is one of the most well-known machine scheduling problems and one of the strongly NP-hard combinatorial optimization problems. Cost optimization is an attractive and critical research and development area for both academic and industrial societies. This paper presents a cost driven model of the job-shop scheduling problem in which the solutions are driven by bu...

The Group Shop Scheduling Problem (GSP) is a generalization of the classical Job Shop and Open Shop Scheduling Problems. In the GSP there are m machines and n jobs. Each job consists of a set of operations, which must be processed on specified machines without preemption. The operations of each job are partitioned into groups on which a total precedence order is given. The problem is to order t...

Flexible Job shop scheduling is very important in production management and combinatorial optimization. It is NP-hard problem and consists of two sub-problems: sequencing and assignment. Multiobjective Flexible Job-Shop Scheduling Problems (MFJSSP) is formulated as three-objective problem which minimizes completion time (makespan), critical machine workload and total work load of all machines. ...