Using the gravitational emulation local search algorithm to solve the multi-objective flexible dynamic job shop scheduling problem in Small and Medium Enterprises

Hosseinabadi, Ali Asghar Rahmani; Siar, Hajar; Shamshirband, Shahaboddin; Shojafar, Mohammad; Nasir, Mohd Hairul Nizam Md

doi:10.1007/s10479-014-1770-8

Cited by 60 publications

(28 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Centralised methods are criticised for being too rigid and very poor at reacting to dynamic situations (Scholz-Reiter, Rekersbrink, and Görges 2010). Recent related works in centralised systems cover advanced search algorithms for similar scenarios; Shamshirband et al investigates a genetic-based open-shop scheduling on considering machine maintenance (Shamshirband et al 2015), additionally Hosseinabadi et al uses a gravitational emulation local search algorithm for multi-objective dynamic job shop scheduling (Hosseinabadi et al 2015). For this study a simple (First In First Out) FIFO heuristic is used to compare hierarchical systems relative to anarchic, this is sufficient to evaluate inherent traits of the two system types.…”

Section: Control Architecturesmentioning

confidence: 99%

Anarchic manufacturing

Nassehi

Snider

2018

International Journal of Production Research

View full text Add to dashboard Cite

This paper introduces anarchic manufacturing, an extremely distributed planning and control philosophy as the methodology for planning and controlling future smart factories. Anarchic manufacturing delegates decision making authority and autonomy to the lowest level of entities in system elements with no centralised control or oversight. It is often postulated that traditional hierarchical structures may not be well suited to manage the state-of-the-art hyper-connected smart factories due to their reliance on communication between management layers. Distributed systems, on the other hand, are commonly perceived to be inherently more flexible, robust and adaptable than hierarchical systems due to their structure. This paper characterises distributed systems by evaluating the relative flexibility of a representative hierarchical system against an anarchic system in a job shop scenario. Multi agent based simulation is used to model both hierarchical and anarchic systems, which are tested for flexibility following the Taguchi method and compared against Taillard's benchmark job shop problems for overall performance. The results show that the anarchic system performs as well as the hierarchical system when subjected to unforeseen disruption, refuting the argument that hierarchical systems are too rigid and distributed systems are inherently more flexible. However, anarchic manufacturing systems, which show adaptability and self-optimising traits, provide a platform to potentially enable the emerging digital manufacturing paradigm through the free market structure especially when bandwidth for communications is limited.

show abstract

Section: Control Architecturesmentioning

confidence: 99%

Anarchic manufacturing

Nassehi

Snider

2018

International Journal of Production Research

View full text Add to dashboard Cite

show abstract

“…Based on fuzzy theory and a genetic algorithm, Shojafar et al [15, 16] presented a hybrid job scheduling approach to assign jobs with reducing total execution time and execution cost in cloud computing. Using the gravitational emulation local search algorithm, Hosseinabadi et al [17] proposed a novel algorithm to solve the job-shop scheduling problem in Small and Medium Enterprises. However, in all of those works, the periods of tasks were not strict and some slack time was allowed between successive instances of a periodic task.…”

Section: Introductionmentioning

confidence: 99%

Scheduling Independent Partitions in Integrated Modular Avionics Systems

Chen

Han

2016

PLoS ONE

View full text Add to dashboard Cite

Recently the integrated modular avionics (IMA) architecture has been widely adopted by the avionics industry due to its strong partition mechanism. Although the IMA architecture can achieve effective cost reduction and reliability enhancement in the development of avionics systems, it results in a complex allocation and scheduling problem. All partitions in an IMA system should be integrated together according to a proper schedule such that their deadlines will be met even under the worst case situations. In order to help provide a proper scheduling table for all partitions in IMA systems, we study the schedulability of independent partitions on a multiprocessor platform in this paper. We firstly present an exact formulation to calculate the maximum scaling factor and determine whether all partitions are schedulable on a limited number of processors. Then with a Game Theory analogy, we design an approximation algorithm to solve the scheduling problem of partitions, by allowing each partition to optimize its own schedule according to the allocations of the others. Finally, simulation experiments are conducted to show the efficiency and reliability of the approach proposed in terms of time consumption and acceptance ratio.

show abstract

“…Although working on static job shop scheduling is a well-known problem in the literature, dynamic events often occur, which needs to be handled to increase the productivity and machine balance rates in a real manufacturing system [98]. Actual manufacturing scheduling models are naturally dynamic which are harder to solve than static models [90,91], because when there is an interruption, proposed plans and schedules should be revised to respond to such dynamic events.…”

Section: Problem Definitionmentioning

confidence: 99%

Solving Integrated Process Planning, Dynamic Scheduling, and Due Date Assignment Using Metaheuristic Algorithms

Erden

Demir

Kökçam

2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Because the alternative process plans have significant contributions to the production efficiency of a manufacturing system, researchers have studied the integration of manufacturing functions, which can be divided into two groups, namely, integrated process planning and scheduling (IPPS) and scheduling with due date assignment (SWDDA). Although IPPS and SWDDA are well-known and solved problems in the literature, there are limited works on integration of process planning, scheduling, and due date assignment (IPPSDDA). In this study, due date assignment function was added to IPPS in a dynamic manufacturing environment. And the studied problem was introduced as dynamic integrated process planning, scheduling, and due date assignment (DIPPSDDA). The objective function of DIPPSDDA is to minimize earliness and tardiness (E/T) and determine due dates for each job. Furthermore, four different pure metaheuristic algorithms which are genetic algorithm (GA), tabu algorithm (TA), simulated annealing (SA), and their hybrid (combination) algorithms GA/SA and GA/TA have been developed to facilitate and optimize DIPPSDDA on the 8 different sized shop floors. The performance comparisons of the algorithms for each shop floor have been given to show the efficiency and effectiveness of the algorithms used. In conclusion, computational results show that the proposed combination algorithms are competitive, give better results than pure metaheuristics, and can effectively generate good solutions for DIPPSDDA problems.

show abstract

Using the gravitational emulation local search algorithm to solve the multi-objective flexible dynamic job shop scheduling problem in Small and Medium Enterprises

Cited by 60 publications

References 25 publications

Anarchic manufacturing

Anarchic manufacturing

Scheduling Independent Partitions in Integrated Modular Avionics Systems

Solving Integrated Process Planning, Dynamic Scheduling, and Due Date Assignment Using Metaheuristic Algorithms

Contact Info

Product

Resources

About