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...

We consider a three-stage dynamic flexible flow shop scheduling problem in which jobs of multiple types arrive dynamically over time, a quality feedback mechanism is present, and the setup timing and the process defect rate are closely related. At each machine in the second stage, a sequence-independent setup operation is necessary to changeover job types. Once a setup is done for a job type at...

The job shop scheduling is an important and complex problem for a manufacturing system. It is well known and popular problem having (Non-Polynomial) NP-hard characteristic to find the optimal or near optimal solution (schedules) quickly. In job shop scheduling a set of “N” number of jobs are processed through an “M” number of given set of machines. It must be processed in the prescribed order b...

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. ...

This paper discusses the scheduling of precedence-related jobs non-preemptively in a job shop environment with an objective of minimizing the makespan. Due to the NP-hard nature of the scheduling problems, it is usually difficult to find an exact optimal schedule and hence one should rely on finding a near to optimal solution. This paper proposes a computationally effective powers-of-two heuris...

An NP-hard problem like Flexible Job Shop Scheduling (FJSP) tends to be more complex and requires computational effort optimize the objectives with contradictory measures. This paper aims address FJSP combined objectives, minimization of make-span, maximum workload, total workload. proposes ‘Hybrid Adaptive Firefly Algorithm’ (HAdFA), a new enhanced version classic Algorithm (FA) embedded adapt...

Ideally, the solution to job-shop scheduling problem (JSP) should effectively reduce cost of manpower and materials, thereby enhancing core competitiveness manufacturer. Deep learning (DL) neural networks have certain advantages in handling complex dynamic JSPs with a massive amount historical data. Therefore, this paper proposes model based on DL. Firstly, data prediction was established for s...

This article addresses the job-shop problem of minimizing the schedule length (makespan) for processing n jobs on two machines with sequence-dependent setup and removal times. The processing of each job includes at most two operations that have to be non-preemptive. Machine routes may differ from job to job. If all setup and removal times are equal to zero, this problem is polynomially solvable...