An Optimization Model for Manufacturing Systems in an Uncertain Environment

2015 ◽  
Author(s):  
Michael Mitnovitsky ◽  
Miri Weiss Cohen ◽  
Moshe Shpitalni
Keyword(s):  
Manufacturing Systems ◽  
Job Shop ◽  
Adaptive Control System ◽  
Operational Flexibility ◽  
Agent Based ◽  
Machine Breakdowns ◽  
Processing Times ◽  
Dynamic Events ◽  
Increase Productivity ◽  
Flexible Job Shop Problem

This paper examines a flexible job shop problem that considers dynamic events, such as stochastic job arrivals, uncertain processing times, unexpected machine breakdowns and the possibility of processing flexibility. To achieve this goal, a new agent-based adaptive control system has been developed at the factory level, along with advanced decision-making strategies that provide responsive factories with adaptation and reconfiguration capabilities and advanced complementary scheduling abilities. The aim is to facilitate operational flexibility and increase productivity as well as offer strategic advantages such as analysis of factory development options by simulation. The feasibility of the proposed system is demonstrated by simulation under various experimental settings, among them shop utilization level, due date tightness and breakdown level.

scholarly journals A New Meta-Heuristic Algorithm for Solving the Flexible Dynamic Job-Shop Problem with Parallel Machines

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 165 ◽  
Author(s):  
Arun Sangaiah ◽  
Mohsen Suraki ◽  
Mehdi Sadeghilalimi ◽  
Seyed Bozorgi ◽  
Ali Hosseinabadi ◽  
...  
Keyword(s):  
Manufacturing Systems ◽  
Parallel Machines ◽  
Job Shop ◽  
Two Dimensional ◽  
Scheduling Problems ◽  
Operational Flexibility ◽  
Machine Failure ◽  
Different Dimensions ◽  
First Time ◽  
Dynamic Job Shop

In a real manufacturing environment, the set of tasks that should be scheduled is changing over the time, which means that scheduling problems are dynamic. Also, in order to adapt the manufacturing systems with fluctuations, such as machine failure and create bottleneck machines, various flexibilities are considered in this system. For the first time, in this research, we consider the operational flexibility and flexibility due to Parallel Machines (PM) with non-uniform speed in Dynamic Job Shop (DJS) and in the field of Flexible Dynamic Job-Shop with Parallel Machines (FDJSPM) model. After modeling the problem, an algorithm based on the principles of Genetic Algorithm (GA) with dynamic two-dimensional chromosomes is proposed. The results of proposed algorithm and comparison with meta-heuristic data in the literature indicate the improvement of solutions by 1.34 percent for different dimensions of the problem.

Scheduling in Flexible Manufacturing Systems

2018 ◽  
pp. 1-19
Author(s):  
Fraj Naifar ◽  
Mariem Gzara ◽  
Taicir Loukil Moalla
Keyword(s):  
Flexible Manufacturing ◽  
Flexible Manufacturing Systems ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Computation Time ◽  
Flexible Job Shop ◽  
Scheduling Problems ◽  
Genetic Operators ◽  
Flexible Job Shop Problem

Flexible manufacturing systems have many advantages like adaptation to changes and reduction of lateness. But flexible machines are expensive. The scheduling is a central functionality in manufacturing systems. Optimizing the job routing through the system, while taking advantage from the flexibility of the machines, aims at improving the system's profitability. The introduction of the flexibility defines a variant of the scheduling problems known as flexible job shop scheduling. This variant is more difficult than the classical job shop since two sub-problems are to be solved the assignment and the routing. To guarantee the generation of efficient schedules in reasonable computation time, the metaheuristic approach is largely explored. Particularly, much research has addressed the resolution of the flexible job shop problem by genetic algorithms. This chapter presents the different adaptations of the genetic scheme to the flexible job shop problem. The solution encodings and the genetic operators are presented and illustrated by examples.

APPROXIMATION ALGORITHMS FOR FLEXIBLE JOB SHOP PROBLEMS

2005 ◽  
Vol 16 (02) ◽  
pp. 361-379 ◽  
Author(s):  
KLAUS JANSEN ◽  
MONALDO MASTROLILLI ◽  
ROBERTO SOLIS-OBA
Keyword(s):  
Manufacturing Systems ◽  
Approximation Scheme ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Linear Time ◽  
Flexible Job Shop ◽  
Job Shop Scheduling Problem ◽  
Time Approximation ◽  
Shop Scheduling ◽  
Flexible Job Shop Problem

The Flexible Job Shop problem is a generalization of the classical job shop scheduling problem in which for every operation there is a group of machines that can process it. The problem is to assign operations to machines and to order the operations on the machines so that the operations can be processed in the smallest amount of time. This models a wide variety of problems encountered in real manufacturing systems. We present a linear time approximation scheme for the non-preemptive version of the problem when the number m of machines and the maximum number μ of operations per job are fixed. We also study the preemptive version of the problem when m and μ are fixed, and present a linear time approximation scheme for the problem without migration and a (2+ε)-approximation algorithm for the problem with migration.

Robust Scheduling for Flexible Job-Shop Problems with Uncertain Processing Times

2015 ◽  
Vol 135 (6) ◽  
pp. 713-720
Author(s):  
Wan-Ling Li ◽  
Tomohiro Murata ◽  
Muhammad Hafidz Fazli bin Md Fauadi
Keyword(s):  
Job Shop ◽  
Flexible Job Shop ◽  
Robust Scheduling ◽  
Processing Times

scholarly journals Ant Colony Intelligence in Flexible Manufacturing Scheduling Using Contract-Net Model

2011 ◽  
Vol 2-3 ◽  
pp. 608-613
Author(s):  
Ying Zi Wei ◽  
Yi Jun Feng ◽  
Kan Feng Gu
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Ant Colony ◽  
Contract Net Protocol ◽  
Agent Based ◽  
Contract Net ◽  
Multi Agent ◽  
Bidding Mechanism ◽  
Alternative Processes ◽  
Alternative Machines

This paper builds an efficient agent-based flexible scheduling for real-world manufacturing systems. Considering the alternative processes and alternative machines, the allocation of manufacturing resources is achieved through negotiation among the job and machine agents in a multi-agent system (MAS). Ant Colony Intelligence (ACI) is proposed to be combined with Contract Net Protocol (CNP) so as to make agents adaptive to changing circumstances. ACI is integrated into both machine agents and job agents to solve the task allocation and sequencing problem. CNP is introduced to allow the agents to cooperate and coordinate their local schedules in order to find globally near-optimal robust schedules. The negotiation protocol is an interactive bidding mechanism based on the hybrid contract net protocol. The implementation of the issues using CNP model is discussed. Experimental results verify the effectiveness and efficiency of the proposed algorithm integrated with ant-inspired coordination.

Sign in / Sign up

Export Citation Format

Share Document