This work studies the performance of two Mixed Integer Linear Programming (MILP) models to solve scheduling problems in a flexible job shop environment with recirculation and assembly using a due-date-based objective function. The models convey different approaches both in the modelling of time (discrete and continuous approaches) as well as in the assignment of jobs to machines. The comparison...

The Flexible Job Shop scheduling Problem (FJSP) is a generalization of the classical Job Shop Problem in which each operation must be processed on a given machine chosen among a finite subset of candidate machines. The aim is to find an allocation for each operation and to define the sequence of operations on each machine so that the resulting schedule has a minimal completion time. We propose ...

Due to the complicated circumstances in workshop, most of the conventional scheduling algorithms fail to meet the requirements of instantaneity, complexity, and dynamicity in job-shop scheduling problems. Compared with the static algorithms, dynamic scheduling algorithms can better fulfill the requirements in real situations. Considering that both flexibility and fuzzy processing time are commo...

In view of the difficulty of obtaining the optimal solution to the multi-objective scheduling of flexible job-shop by the general genetic algorithm, this paper takes into account the shortest processing time and the balanced use of machines, and puts forward the multi-population genetic algorithm based on the multi-objective scheduling of flexible job-shop. The method attempts to minimize the l...

Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. A Variable Neighborhood Genetic Algorithm (VNGA) is proposed for the problem with makespan criterion, consisting of a combination of the variable neighborhood search (VNS) and genetic algorithm (GA). Variable ne...

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...

Flexible manufacturing systems (FMSs) are nowadays installed in the mechanical industry. In such systems. many different part types are produced simultaneously and it is necessary to take tooling constraints into account for finding an optimal schedule. A heuristic method is presented for solving the m-machine, n-job shop scheduling problem with tooling constraints. This method. named TOMATO, i...

Purpose To investigate the efficiency of a discretization procedure utilizing a time-indexed mathematical optimization model for finding accurate solutions to flexible job shop scheduling problems considering objectives comprising makespan and tardiness, respectively. Design/methodology/approach A time-indexed mixed integer programming model is used to find solutions by iteratively employing ti...

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. ...

An extended version of the flexible job shop problem is tackled in this work. The considered extension to the classical flexible job shop problem allows the precedences between the operations to be given by an arbitrary directed acyclic graph instead of a linear order. Therefore, the problem consists of allocating the operations to the machines and sequencing them in compliance with the given p...