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 evolutionary algorithm is proposed to obtain a large set of Pareto-op...

In this paper, we propose an energy-efficient mathematical model for the resource-constrained project scheduling problem to optimize makespan and consumption of energy, simultaneously. In the proposed model, resources are speed-scaling machines. The problem is NP-hard in the strong sense. Therefore, a multi-objective fruit fly optimization algorithm (MOFOA) is developed. The MOFOA uses the VIKO...

In this paper, we propose a novel hybrid variable neighborhood search algorithm combining with the genetic algorithm (VNS+GA) for solving the multi-objective flexible job shop scheduling problems (FJSPs) to minimize the makespan, the total workload of all machines, and the workload of the busiest machine. Firstly, a mix of two machine assignment rules and two operation sequencing rules are deve...

The purpose of Grid computing is to utilize computational power of idle resources which are distributed in different areas. Given the grid dynamism and its decentralize resources, there is a need for an efficient scheduler for scheduling applications. Since task scheduling includes in the NP-hard problems various researches have focused on invented algorithms especially the genetic ones. But si...

A computationally e ective heuristic method for solving the minimum makespan problem of job shop scheduling is presented. The proposed local search method is based on a tabu search technique and on the shifting bottleneck procedure used to generate the initial solution and to re ne the next-current solutions. Computational experiments on a standard set of problem instances show that, in several...

Scheduling problems are a paradigm of CSP. In this paper we present a number of techniques to solve them by means of Genetic Algorithms. Firstly we consider conventional Genetic Algorithms and then we demonstrate that their performance really improves when used together with other techniques such as dispatching rules, probability based heuristics or local search. We report results from an exper...

this paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. in the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). however,, two significant criteria for each schedule in stochastic models are: expectable m...