in this paper, we propose an iterated greedy algorithm for solving the blocking flow shop scheduling problem with total flow time minimization objective. the steps of this algorithm are designed very efficient. for generating an initial solution, we develop an efficient constructive heuristic by modifying the best known neh algorithm. effectiveness of the proposed iterated greedy algorithm is t...

This research combines between two different manufacturing concepts. On the one hand, flow shop scheduling is a well-known problem in production systems. The problem appears when a group of jobs shares the same processing sequence on two or more machines sequentially. Flow shop scheduling tries to find the appropriate solution to optimize the sequence order of this group of jobs over the existi...

A discrete event simulation model was developed to study the flow of material and product in a shop floor. It uses real time data available from a job shop sole dedicated to noncommercial contracts and as such deals with very seasonal demand. The objective of this model is to provide the shop with a decision support tool that will assist in evaluating the movement of products throughout the sho...

Based on MATLAB/SimEvents simulation platform and genetic algorithm, the simulation and optimization of energy consumption in hybrid flow shop is studied. Considering workshop layout and workpiece path, machining process simulation in hybrid flow shop is realized. With the processing time, processing power and stand-by power introduced into simulation model, the energy consumption simulation in...

In shop scheduling, several applications exist where it is required that some components perform consecutively. We refer to no-idle schedules if machines are required to operate with no inserted idle time and no-wait schedules if tasks cannot wait between the end of an operation and the start of the following one. We consider here no-idle/no-wait shop scheduling problems with makespan as perfor...

This paper proposes an effective multi-objective differential evolution algorithm (MDES) to solve a permutation flow shop scheduling problem (PFSSP) with modified Dejong's learning effect. The proposed algorithm combines the basic differential evolution (DE) with local search and borrows the selection operator from NSGA-II to improve the general performance.  First the problem is encoded with a...

This paper presents an investigation of scheduling procedures to seek the minimum of a positively weighted convex sum of makespan and the number of tardy jobs in a static flexible flow shop scheduling environment. The flexible flow shop problem is a scheduling of jobs in a flow shop environment consisting of series of production stages, some of which may have only one machine, but at least one ...

In this paper, we address the problem of finding a permutation schedule of n jobs in an m machine flow-shop environment that minimizes the maximum completion time Cmax (Makespan) of all jobs. The jobs are available at time zero and have sequence-dependent setup times on each machine. All parameters, such as processing and setup times, are assumed to be known with certainty. This problem is clas...