This paper tackles the flexible job-shop scheduling problem with uncertain processing times. The uncertainty in processing times is represented by means of fuzzy numbers, hence the name fuzzy flexible job-shop scheduling. We propose an effective genetic algorithm hybridised with tabu search and heuristic seeding to minimise the total time needed to complete all jobs, known as makespan. To build...

Using ratings of hypothetical job applicants with and without a disability obtained from both fulltime workers (n = 88) and undergraduates (n = 98), we examined the effects of disability (paraplegia, epilepsy, clinical depression, or non-disabled), gender, and nature of the job (supervisory or non-supervisory) on five jobrelevant dependent measures. Contrary to our hypothesis, applicants with a...

Originally, MapReduce implementations such as Hadoop employed First In First Out (fifo) scheduling, but such simple schemes cause job starvation. The Hadoop Fair Scheduler (hfs) is a slot-based MapReduce scheme designed to ensure a degree of fairness among the jobs, by guaranteeing each job at least some minimum number of allocated slots. Our prime contribution in this paper is a different, fle...

Keywords: Scheduling Flexible job shop Differential evolution Local search Neighborhood structure Makespan a b s t r a c t This paper proposes hybrid differential evolution (HDE) algorithms for solving the flexible job shop scheduling problem (FJSP) with the criterion to minimize the makespan. Firstly, a novel conversion mechanism is developed to make the differential evolution (DE) algorithm t...

Flexible assembly job shop scheduling has been proved to be an NP-hard problem. To reduce the complexity, it is always divided into 2 sub-problems: routing sub-problem and sequencing sub-problem. In this paper, in order to develop a solution with high accuracy, we propose a method that can deal with these two sub-problems concurrently. Tabu search, one of the meta-heuristics, is adopted. Some e...

We present a heuristic algorithm for solving the scheduling problem in a glass factory. It is basically a flexible job shop problem, with some added complexities due to the special characteristics of the machines involved in the production process. The main objective function is a non-convex function of completion times and duedates, and some secondary objectives are also considered.

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...

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, 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...