scholarly journals An enhanced Tabu search Cell formation Algorithm for Cellular Manufacturing System

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Tabu Search ◽  
Hybrid Algorithm ◽  
Manufacturing Systems ◽  
Cellular Manufacturing ◽  
Search Algorithm ◽  
Cell Formation ◽  
Primary Objective ◽  
Intracellular Movement ◽  
Multiple Routes ◽  
Machine Cell

The major benefit of using Cellular manufacturing systems (CMS) is the improvement in efficiency and reduction in the production time. In a CMS the part families and machine parts are identified to minimise the inter and intracellular movement and maximise the utilisation of machines within each cell. Many scholars have proposed methods for the evaluation of machine cell part layouts with single routes; this paper introduces a modified Hybrid Tabu Search Algorithm (HTSA) referred to as Hybrid Algorithm in this study for machine cell part layouts having multiple routes as well. The primary objective of this paper is to minimise the inter and intracellular movement using a hybrid algorithm. The paper presents a comparative analysis of the existing and the proposed algorithms, proving that the proposed hybrid algorithm is simple, easy to understand, and has a remarkable efficiency with a runtime of 5.6 seconds.

Cellular manufacturing systems design using Tabu search

2000 ◽  
Vol 214 (2) ◽  
pp. 169-172 ◽  
Author(s):  
G V Songore ◽  
V Songore
Keyword(s):  
Tabu Search ◽  
Manufacturing Systems ◽  
Family Formation ◽  
Cellular Manufacturing ◽  
Cell Formation ◽  
Real Life ◽  
Systems Design ◽  
Computational Time ◽  
Cellular Manufacturing Systems ◽  
Manufacturing Systems Design

Several techniques have appeared in the literature for the cell formation problem. However, most of these heuristics have the disadvantages that they cannot solve real-life problems typical of manufacturing firms in reasonable computational time, and deal with the part family formation and cell grouping problems separately. The Tabu search meta-heuristic is presented for resolving these problems. The minimization of intercellular movements as an objective function is demonstrated, although minimization of cell load variation and the multiobjective function option exist in the procedure developed. The results discussed for some problems taken from the literature show that the Tabu search is a promising technique for solving the cellular manufacturing systems design problem for both medium and large problem instances.

Multidisciplinary Machine Cell Formation for Design of Cellular Manufacturing Systems

1999 ◽  
Author(s):  
David He ◽  
Angela Adamyan
Keyword(s):  
System Reliability ◽  
Utility Theory ◽  
Manufacturing Systems ◽  
Cellular Manufacturing ◽  
Cell Formation ◽  
Cellular Manufacturing Systems ◽  
Design Attributes ◽  
Multi Attribute Utility Theory ◽  
New Formulation ◽  
Machine Cell

Abstract Machine cell formation in design of cellular manufacturing systems has traditionally ignored the issues of reliability. As such, the machine cell formation methods have been developed without the explicit considerations of system reliability and maintainability and the systems designed by these methods may have poor reliability and maintainability and hence result in low availability and productivity. In this paper, we discussed how the reliability issues should be incorporated into solving machine cell formation problems. A new formulation for machine cell formation with reliability considerations in cellular manufacturing systems was developed. The formulation is based on multi-attribute utility theory and represents the tradeoff the designers are willing to make between reliability and other design attributes in design of cellular manufacturing systems. An example was used to illustrate the application of the formulation for machine cell formation with reliability considerations. An algorithm for determining the optimal machine cell size in design of cellular manufacturing systems is also proposed.

Cell formation and scheduling of part families for reconfigurable cellular manufacturing systems using Tabu search

SIMULATION ◽  
2013 ◽  
Vol 89 (9) ◽  
pp. 1056-1072 ◽  
Author(s):  
Ignacio Eguia ◽  
Jesus Racero ◽  
Fernando Guerrero ◽  
Sebastian Lozano
Keyword(s):  
Tabu Search ◽  
Manufacturing Systems ◽  
Cellular Manufacturing ◽  
Cell Formation ◽  
Cellular Manufacturing Systems ◽  
Part Families

scholarly journals A Hybrid Ant Colony System and Tabu Search algorithm for the production planning of dynamic cellular manufacturing systems while confronting uncertain costs

2018 ◽  
Vol 15 (4) ◽  
pp. 499-516
Author(s):  
Aidin Delgoshaei ◽  
Abolfazl Mirzazadeh ◽  
Ahad Ali
Keyword(s):  
Tabu Search ◽  
Manufacturing Systems ◽  
Inflation Rate ◽  
Cellular Manufacturing ◽  
Search Algorithm ◽  
Ant Colony ◽  
Ant Colony System ◽  
Total System ◽  
Tabu Search Algorithm ◽  
Cellular Manufacturing Systems

Highlights: Cellular Manufacturing systems cover a wide range of industries. Inflation rate can impose financial harms on cellular manufacturing systems. The over-allocation of workers, which usually happens in dynamic systems, causes reduction of the system performance. The proposed algorithm in this research can successfully schedule cellular systems to reduce system costs. Goal: The main aim is to determine the best trade-off values between in-house manufacturing and outsourcing, and track the impact of uncertain costs on gained schedules. To be more comprehensive, the performance of human resources is restricted and the partial demands are considered uncertain. Design / Methodology / Approach: In this paper a new method for minimizing human resource costs, including operating, salary, hiring, firing, and outsourcing in a dynamic cellular manufacturing system is presented where all system costs are uncertain during manufacturing periods and can be affected by inflation rate. For this purpose, a multi-period scheduling model that is flexible enough to use in real industries has been proposed. To solve the proposed model, a hybrid Ant Colony Optimization and the Tabu Search algorithm (ACTS) are proposed and the outcomes are compared with a Branch-and-Bound based algorithm. Results: Our findings showed that the inflation rate has significant effect on multi-period system planning. Moreover, utilizing system capability by the operator, for promoting and using temporary workers, can effectively reduce system costs. It is also found that workers’ performance has significant effect on total system costs. Limitations of the investigation: This research covers the cellular manufacturing systems. Practical implications: The algorithm is applied for 17 series of dataset that are found in the literature. The proposed algorithm can be easily applied in real industries. Originality / Value: The authors confirm that the current research and its results are original and have not been published before. The proposed algorithm is useful to schedule cellular manufacturing systems and analyse various production conditions.

Cell Formation and Part Family Identification by Using Traditional Methods

2016 ◽  
Vol 854 ◽  
pp. 121-126 ◽  
Author(s):  
M. Shunmuga Sundaram ◽  
V. Anbumalar ◽  
P. Anand ◽  
B. Aswinkumar
Keyword(s):  
Manufacturing Systems ◽  
Cellular Manufacturing ◽  
Rank Order ◽  
Cell Formation ◽  
Second Phase ◽  
Single Linkage ◽  
Part Family ◽  
Part Families ◽  
Machine Cell ◽  
Combined Algorithm

A Combined Algorithm is proposed to form the machine cell and part family identification in the cellular manufacturing system. In the first phase, part families identification, by using Rank Order Clustering (ROC) and Modified Single Linkage Clustering (MOD-SLC). In second phase, Machine cell formation, by using Rank Order Clustering (ROC) and Modified Single Linkage Clustering (MOD-SLC), which is to assign machines into machine cells to produce part families. The above Proposed method is tested by using standard problems and compared with other method results for the same standard problems. Grouping efficiency is one of the most widely used measures of quality for Cellular Manufacturing Systems.

scholarly journals GASAT: A Genetic Local Search Algorithm for the Satisfiability Problem

2006 ◽  
Vol 14 (2) ◽  
pp. 223-253 ◽  
Author(s):  
Frédéric Lardeux ◽  
Frédéric Saubion ◽  
Jin-Kao Hao
Keyword(s):  
Tabu Search ◽  
Local Search ◽  
Hybrid Algorithm ◽  
State Of The Art ◽  
Search Algorithm ◽  
Satisfiability Problem ◽  
Local Search Algorithm ◽  
Overall Performance ◽  
Genetic Local Search ◽  
Search Stage

This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossover and a tabu search stage. We have conducted experiments to evaluate the different components of GASAT and to compare its overall performance with state-of-the-art SAT algorithms. These experiments show that GASAT provides very competitive results.

scholarly journals Modeling the Scheduling Problem in Cellular Manufacturing Systems Using Genetic Algorithm as an Efficient Meta-Heuristic Approach

2021 ◽  
Author(s):  
Amin Rezaeipanah ◽  
Musa Mojarad
Keyword(s):  
Genetic Algorithm ◽  
Manufacturing Systems ◽  
Cellular Manufacturing ◽  
Programming Model ◽  
Heuristic Method ◽  
Cell Formation ◽  
Mixed Integer ◽  
Test Problems ◽  
Cellular Manufacturing Systems ◽  
Machine Grouping

This paper presents a new, bi-criteria mixed-integer programming model for scheduling cells and pieces within each cell in a manufacturing cellular system. The objective of this model is to minimize the makespan and inter-cell movements simultaneously, while considering sequence-dependent cell setup times. In the CMS design and planning, three main steps must be considered, namely cell formation (i.e., piece families and machine grouping), inter and intra-cell layouts, and scheduling issue. Due to the fact that the Cellular Manufacturing Systems (CMS) problem is NP-Hard, a Genetic Algorithm (GA) as an efficient meta-heuristic method is proposed to solve such a hard problem. Finally, a number of test problems are solved to show the efficiency of the proposed GA and the related computational results are compared with the results obtained by the use of an optimization tool.

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