The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. This paper presents a hybrid artificial immune system for the JSSP with the objective of minimizing makespan. The proposed approach combines the artificial immune system, which has a powerful global exploration capability, with the local search method, which can exploit the optimal antibody....

Scheduling is an important process widely used in manufacturing, production, management, computer science, and so on. Appropriate scheduling can reduce material handling costs and time. Finding good schedules for given sets of jobs can thus help factory supervisors effectively control job flows and provide solutions for job sequencing. In simple flow shop problems, each machine operation center...

Job Shop scheduling problem has significant importance in many researching fields such as production management and programming and also combined optimizing. Job Shop scheduling problem includes two sub-problems: machine assignment and sequence operation performing. In this paper combination of particle swarm optimization algorithm (PSO) and gravitational search algorithm (GSA) have been presen...

Re-entrant scheduling is an important search problem with many constraints in the flow shop. In the literature, a number of approaches have been investigated from exact methods to meta-heuristics. This paper presents a genetic algorithm that encodes the problem as multi-level chromosomes to reflect the dependent relationship of the re-entrant possibility and resource consumption. The novel enco...

This paper deals with performance evaluation and scheduling problems in m machine stochastic flow shop with unlimited buffers. The processing time of each job on each machine is a random variable exponentially distributed with a known rate. We consider permutation flow shop. The objective is to find a job schedule which minimizes the expected makespan. A classification of works about stochastic...

This paper presents a multi agent system for the job shop scheduling problems. The proposed system consists of initial scheduling agent, search agents, and schedule management agent. In initial scheduling agent, a modified Shifting Bottleneck is proposed. That is, an effective heuristic approach and can generate a good solution in a low computational effort. In search agents, a hybrid search ap...

In this study, a distributed flow shop scheduling problem with batch delivery constraints is investigated. The objective to minimize the makespan and energy consumptions simultaneously. To end, hybrid algorithm combining wale optimization (WOA) local search heuristics developed. proposed algorithm, each solution represented by three vectors, namely job sequence vector, assignment factory vector...

We propose an enhanced depthrst heuristic search algorithm to face the job shop scheduling problem with operators. This problem extends the classical job shop scheduling problem by considering a limited number of human operators that assist the processing of the operations. We considered total ow time minimization as objective function which makes the problem harder to solve and more interestin...

Flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem. FJSP is NP-hard and mainly presents two difficulties. The first one is to assign each operation to a machine out of a set of capable machines, and the second one deals with sequencing the assigned operations on the machines. This paper proposes a parallel variable neighborhood search (PVNS)...

We consider the fuzzy job shop problem, where uncertain durations are modelled as fuzzy numbers and the objective is to minimise the expected makespan. A recent local search method from the literature has proved to be very competitive when used in combination with a genetic algorithm, but at the expense of a high computational cost. Our aim is to improve its efficiency with an alternative resch...