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. It is quite difficult to achieve optimal or near-optimal solutions with single traditional optimization approach because the multi objective FJSP has the high computational complexity. An novel hybrid algorithm ...

In this paper, we propose a new optimization technique, the hierarchical multi-space competitive distributed genetic algorithm (HmcDGA), which is effective for the hierarchical optimization problem. It is an extension of the multi-space competitive distributed genetic algorithm (mcDGA), which was proposed by the authors. The mcDGA efficiently finds an optimal solution with a low computational c...

This paper presents a meta-heuristic algorithm for solving the Flexible Job Shop Scheduling Problem (FJSSP). This strategy, known as Iterative Flattening Search (IFS), iteratively applies a relaxationstep, in which a subset of scheduling decisions are randomly retracted from the current solution; and a solving-step, in which a new solution is incrementally recomputed from this partial schedule....

As the Flexible Job Shop Scheduling Problem (or FJSP) is strongly NP-hard, using an evolutionary approach to find near-optimal solutions requires effective chromosome representations as well as carefully designed parameters for crossover and mutation to achieve efficient search. This paper proposes a new chromosome representation and a design of related parameters to solve the FJSP efficiently....

We propose the new framework of the distributed tabu search metaheuristic designed to be executed using a multi-GPU cluster, i.e. cluster of nodes equipped with GPU computing units. We propose a hybrid single-walk parallelization of the tabu search, where hybridization consists in examining a number of solutions from a neighborhood concurrently by several GPUs (multi-GPU). The methodology is de...

A parallel approach to flexible job shop scheduling problem is presented in this paper. We propose two double-level parallel metaheuristic algorithms based on the new method of the neighborhood determination. Algorithms proposed here include two major modules: the machine selection module refer to executed sequentially, and the operation scheduling module executed in parallel. On each level a m...

In manufacturing area, the most difficult problems related to the time-efficiency frequently occur if the jobs to be scheduled are heterogeneous, if there are alternative routes on the machines for the jobs and multiple objectives are imposed. This framework, named Multi-Objective Flexible Job Shop Scheduling Problems (MOFJSSP), has been formalized, modeled and studied in the last decades from ...

This paper addresses the flexible job shop scheduling problem with sequence-dependent setup times (SDSTFJSP). This is an extension of the classical job shop scheduling problem with many applications in real production environments. We propose an effective neighborhood structure for the problem, including feasibility and non improving conditions, as well as procedures for fast neighbor estimatio...

Planning and scheduling are as decision making processes which they have important roles in production systems and industries. According that, job shop scheduling is one of NPhard problems to solve multi-objective decision making approaches. So, the problem is known as uncertain with many variables in optimal solution view. Finding optimal solutions are essential task in scheduling of jobs betw...

The major theme of this thesis is the mathematical optimization modelling of the flexible job shop scheduling problem. This problem is present in the so-called multitask cell—a production cell at GKN Aerospace’s facility located in Trollhättan, Sweden—which has served as a case study during the work with this thesis. The thesis consists of two parts, of which the first considers the major theme...