The introduction of NVidia’s powerful Tesla GPU hardware and Compute Unified Device Architecture (CUDA) platform enable many-core parallel programming. As a result, existing algorithms implemented on a GPU can run many times faster than on modern CPUs. Relatively little research has been done so far on GPU implementations of discrete optimisation algorithms. In this paper, two approaches to par...

This paper investigates an approach to the permutation flowshop scheduling problem based on Tabu Search with an additional memory structure called a ‘pruning pattern list’. The pruning pattern list approach allows a better use of the critical block information. A solution of the flowshop scheduling problem is represented by a permutation of job numbers. A pruning pattern is generated from a sol...

This research deals with a flexible flowshop scheduling problem with arrival and delivery of jobs in groups and processing them individually. Due to the special characteristics of each job, only a subset of machines in each stage is eligible to process that job. The objective function deals with minimization of sum of the completion time of groups on one hand and minimization of sum of the diff...

This paper focuses on a two-machine re-entrant flowshop scheduling problem with the objective of minimizing makespan. In the re-entrant flowshop considered here, all jobs must be processed twice on each machine, that is, each job should be processed on machine 1, machine 2 and then machine 1 and machine 2. We develop dominance properties, lower bounds and heuristic algorithms for the problem, a...

There are numerous instances of flowshop in the production process of process industry. When such characteristics as continuous production resulted from high-temperature environment or deteriorate intermediate products are took into consideration, it should be ensured that the waiting time of any job between two consecutive machines is not greater than a given value, which results in the flowsh...

Focusing on the just-in-time (JIT) operations management, earliness as well as, tardiness of jobs’ production and delivery should be discouraged. In accordance to this philosophy, scheduling problems involving earliness and tardiness penalties are very critical for the operations manager. In this paper, a new population heuristic based on the particle swarm optimization (PSO) technique is prese...

Order acceptance and scheduling decisions arise when the limited production capacity entails a manufacturer to select among incoming orders. In this paper, we consider an order acceptance and scheduling problem in a single machine environment where the orders are processed without preemption and a sequence dependent setup time is incurred between processing of every consecutive order. The probl...

A hybrid Taguchi-based genetic algorithm (HTGA) is developed for solving multi-objective flowshop scheduling problems (FSPs). Search performance is improved by using Taguchi-based crossover to avoid scheduling conflicts, and dynamic weights are randomly selected by a fuzzy inference system. The conventional approach to selecting dynamic weights randomly ignores small value for the objective whe...

One of the most important assumptions in production scheduling is that the machines are permanently available without any breakdown. In the real world of scheduling, machines can be made unavailable due to various reasons such as preventive maintenance and unpredicted breakdown. In this paper, we explore flowshop configuration under the assumption of condition-based maintenance to minimize expe...

This paper investigates the single-machine due-window assignment scheduling with truncated learning effects and past-sequence-dependent setup times simultaneously. The scheduler has option of job-rejection, i.e., some jobs are processed other rejected. Under three (i.e., common, slack different) methods, our goal is to minimize sum a general earliness-tardiness cost weighted earliness-tardiness...