Job-shop scheduling problem is one of the most important fields in manufacturing optimization where a set of n jobs must be processed on a set of m specified machines. Each job consists of a specific set of operations, which have to be processed according to a given order. The Flexible Job Shop problem (FJSP) is a generalization of the above-mentioned problem, where each operation can be proces...

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...

The no-wait job shop problem (NWJS-R) considered here is a version of the job shop scheduling problem where, for any two operations of a job, a fixed time lag between their starting times is prescribed. Also, sequencedependent set-up times between consecutive operations on a machine can be present. The problem consists in finding a schedule that minimizes a general regular objective function. W...

Iterative Flattening search is a local search schema introduced for solving scheduling problems with a makespan minimization objective. It is an iterative two-step procedure, where on each cycle of the search a subset of ordering decisions on the critical path in the current solution are randomly retracted and then recomputed to produce a new solution. Since its introduction, other variations h...

Flexible manufacturing system (FMS) scheduling is one of the most trusted and complicated task in machine scheduling. It is strongly Non polynomial complete combinatorial problem. FMS is agile and flexible which is well suited for simultaneous production of a wide variety of product mix in low volumes. Meta-heuristic approaches such as genetic algorithm, simulated annealing etc. are widely appl...

Flexible job-shop scheduling problem (FJSP) in the field of production scheduling presents a quite difficult combinatorial optimization problem. Machines are mostly considered to be the only resource in many research projects dealing with FJSP. In actual production, there are many other factors which influence production scheduling, such as transportation, storage and detection. If machines are...

Since their introduction, local search algorithms – and in particular tabu search algorithms – have consistently represented the state-of-the-art in solution techniques for the classical job-shop scheduling problem. This is despite the availability of powerful search and inference techniques for scheduling problems developed by the constraint programming community. In this paper, we introduce a...

In this paper, we deal with the Job-shop with Multi-Purpose Machine scheduling problem with Availability Constraints (JMPMAC). In the first part, we propose a heuristic, based on priority rules to solve the assignment problem. A local search algorithm is then introduced to improve this assignment solution. In the second part, we introduce a genetic algorithm to solve the sequencing problem. Fin...

A meta-heuristic approach for solving the flexible job-shop scheduling problem (FJSP) is presented in this study. This problem consists of two sub-problems, the routing problem and the sequencing problem and is among the hardest combinatorial optimization problems. We propose a Evolutionary Algorithm (EA) for the FJSP. Our algorithm uses several different rules for generating the initial popula...

In this paper flexible job-shop scheduling problem (FJSP) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. As the problem belongs to the class of NP-Hard problems, a new hybrid genetic algorithm is proposed to obtain a large set of Paretooptimal s...