scholarly journals A Mathematical Programming Model for Cell Formation Problem with Machine Replication

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Reza Raminfar ◽  
Norzima Zulkifli ◽  
Mohammadreza Vasili
Keyword(s):  
Mathematical Programming ◽  
Programming Model ◽  
Cell Formation ◽  
Performance Measure ◽  
Cell Formation Problem ◽  
Mathematical Programming Model ◽  
Solution Quality ◽  
Formation Problem ◽  
Proposed Model ◽  
Size Limits

Cell formation (CF) is a crucial aspect in the design of cellular manufacturing (CM) systems. This paper develops a comprehensive mathematical programming model for the cell formation problem, where product demands, cell size limits, sequence of operations, multiple units of identical machines, machine capacity, or machine cost are all considered. In this model, the intercell moves are restricted to be unidirectional from one cell to the downstream cells, without backtracking. The proposed model is investigated through several numerical examples. To evaluate the solution quality of the proposed model, it is compared with some well-known cell formation methods from the literature, by using group capability index (GCI) as a performance measure. The results and comparisons indicate that the proposed model produces solution with a higher performance.

Genetic vs. Hybrid Algorithm in Process of Cell Formation

2013 ◽  
pp. 68-98 ◽  
Author(s):  
R. Sudhakra Pandian ◽  
Pavol Semanco ◽  
Peter Knuth
Keyword(s):  
Hybrid Algorithm ◽  
Flow Analysis ◽  
Cell Formation ◽  
Performance Measure ◽  
Cell Formation Problem ◽  
Production Flow ◽  
Linkage Algorithm ◽  
Formation Problem ◽  
Exceptional Elements ◽  
Performance Results

The cell formation problem has met with a significant amount of attention in recent years by demonstrating great potential for productivity improvements in production environment. Therefore, the researchers have been developing various methods based on similarity coefficient (SC), graph theory approaches, neural networks (NN), and others with aim to automate the whole cell formation process. This chapter focuses on presentation of hybrid algorithm (HA) and genetic algorithm that are helpful in production flow analysis to solve the cell formation problem. The evaluation of hybrid and genetic algorithms are carried out against the K-means algorithm and C-linkage algorithm that are well known from the literature. The comparison uses performance measure and the total number of exceptional elements (EEs) in the block-diagonal structure of machine-part incidence matrix using operational time as an input. The final performance results are presented in the form of graphs.

Manufacturing cell formation with flexible processing capabilities and worker assignment: Comparison of constraint programming and integer programming approaches

2017 ◽  
Vol 232 (11) ◽  
pp. 2054-2068 ◽  
Author(s):  
Adil Baykasoğlu ◽  
Şeyda Topaloğlu ◽  
Filiz Şenyüzlüler
Keyword(s):  
Integer Programming ◽  
Constraint Programming ◽  
Manufacturing Systems ◽  
High Efficiency ◽  
Programming Model ◽  
Cell Formation ◽  
Programming Approach ◽  
Cell Formation Problem ◽  
Formation Problem ◽  
Complex Constraints

Cell formation deals with grouping of machines and parts in manufacturing systems according to their compatibility. Manufacturing processes are surrounded with an abundance of complex constraints which should be considered carefully and represented clearly for obtaining high efficiency and productivity. Constraint programming is a new approach to combinatorial optimization and provides a rich language to represent complex constraints easily. However, the cell formation problems are well suited to be solved by constraint programming approach since the problem has many constraints such as part-machine requirements, availabilities in the system in terms of capacity, machine and worker abilities. In this study, the cell formation problem is modeled using machine, part processing and worker flexibilities via resource element–based representation. Resource elements define the processing requirements of parts and processing capabilities of machines and workers, which are resource-independent capability units. A total of 12 case problems are generated, and different search phases of constraint programming are defined for the solution procedure. The cell formation problem is modeled in both constraint programming and integer programming, and a comparative analysis of constraint programming and integer programming model solutions is done. The results indicate that both the models are effective and efficient in the solution of the cell formation problem.

scholarly journals Note on a comparative evaluation of nine well-known algorithms for solving the cell formation problem in group technology

2001 ◽  
Vol 5 (4) ◽  
pp. 253-268 ◽  
Author(s):  
Prafulla Joglekar ◽  
Q. B. Chung ◽  
Madjid Tavana
Keyword(s):  
Group Technology ◽  
Cell Formation ◽  
Prima Facie ◽  
Performance Measure ◽  
Specific Situation ◽  
Cell Formation Problem ◽  
Future Studies ◽  
Formation Problem ◽  
A Cell ◽  
Grouping Efficiency

Over the last three decades, numerous algorithms have been proposed to solve the work-cell formation problem. For practicing manufacturing managers it would be nice to know as to which algorithm would be most effective and efficient for their specific situation. While several studies have attempted to fulfill this need, most have not resulted in any definitive recommendations and a better methodology of evaluation of cell formation algorithms is urgently needed. Prima facie, the methodology underlying Miltenburg and Zhang's (M&Z) (1991) evaluation of nine well-known cell formation algorithms seems very promising. The primary performance measure proposed by M&Z effectively captures the objectives of a good solution to a cell formation problem and is worthy of use in future studies. Unfortunately, a critical review of M&Z's methodology also reveals certain important flaws in M&Z's methodology. For example, M&Z may not have duplicated each algorithm precisely as the developer(s) of that algorithm intended. Second, M&Z's misrepresent Chandrasekharan and Rajagopalan's [C&R's] (1986) grouping efficiency measure. Third, M&Z's secondary performance measures lead them to unnecessarily ambivalent results. Fourth, several of M&Z's empirical conclusions can be theoretically deduced. It is hoped that future evaluations of cell formation algorithms will benefit from both the strengths and weaknesses of M&Z's work.

Optimization of the assignment of tickets for railway networks with large passenger flows

2016 ◽  
Vol 232 (2) ◽  
pp. 632-642
Author(s):  
Xuehao Zhai ◽  
Jiahui Zhao ◽  
Qun Chen
Keyword(s):  
Mathematical Programming ◽  
Programming Model ◽  
Transportation Networks ◽  
Capacity Constraints ◽  
Mathematical Programming Model ◽  
Railway Transportation ◽  
Numerical Example ◽  
Proposed Model ◽  
Railway Networks ◽  
Passenger Flows

For railway transportation networks that serve traffic demands for many origin–destination pairs and consist of many railway lines that provide passengers with different choices, this paper proposes a mathematical programming model for optimizing the assignment of tickets among the sections of railway lines. The purpose of the model is to maximize the total passenger turnover or the total number of transported passengers within the capacity constraints of vehicles. A typical numerical example, solved using the linear interactive and general optimizer solver, has been designed to illustrate the proposed model. In addition, the ticket assignment schemes based on different goals are compared.

scholarly journals The Machine-Part Cell Formation Problem with Non-Binary Values: A MILP Model and a Case of Study in the Accounting Profession

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1768
Author(s):  
Jose Joaquin del Pozo-Antúnez ◽  
Francisco Fernández-Navarro ◽  
Horacio Molina-Sánchez ◽  
Antonio Ariza-Montes ◽  
Mariano Carbonero-Ruz
Keyword(s):  
Greedy Algorithm ◽  
Machine Part ◽  
Incidence Matrix ◽  
Cell Formation ◽  
Mixed Integer ◽  
Cell Formation Problem ◽  
Formation Problem ◽  
Real World Problem ◽  
Proposed Model ◽  
The One

The traditional machine-part cell formation problem simultaneously clusters machines and parts in different production cells from a zero–one incidence matrix that describes the existing interactions between the elements. This manuscript explores a novel alternative for the well-known machine-part cell formation problem in which the incidence matrix is composed of non-binary values. The model is presented as multiple-ratio fractional programming with binary variables in quadratic terms. A simple reformulation is also implemented in the manuscript to express the model as a mixed-integer linear programming optimization problem. The performance of the proposed model is shown through two types of empirical experiments. In the first group of experiments, the model is tested with a set of randomized matrices, and its performance is compared to the one obtained with a standard greedy algorithm. These experiments showed that the proposed model achieves higher fitness values in all matrices considered than the greedy algorithm. In the second type of experiment, the optimization model is evaluated with a real-world problem belonging to Human Resource Management. The results obtained were in line with previous findings described in the literature about the case study.

scholarly journals A Comprehensive Mathematical Programming Model for Minimizing Costs in A Multiple-Item Reverse Supply Chain with Sensitivity Analysis

2014 ◽  
Vol 5 (3) ◽  
pp. 42-52
Author(s):  
Hoda Mahmoudi ◽  
Hamed Fazlollahtabar
Keyword(s):  
Sensitivity Analysis ◽  
Supply Chain ◽  
Mathematical Programming ◽  
Programming Model ◽  
Continuous Process ◽  
Reverse Supply Chain ◽  
Distribution Centers ◽  
Mathematical Programming Model ◽  
Proposed Model ◽  
Multiple Item

Abstract These instructions give you guidelines for preparing papers for IFAC conferences. A reverse supply chain is configured by a sequence of elements forming a continuous process to treat return-products until they are properly recovered or disposed. The activities in a reverse supply chain include collection, cleaning, disassembly, test and sorting, storage, transport, and recovery operations. This paper presents a mathematical programming model with the objective of minimizing the total costs of reverse supply chain including transportation, fixed opening, operation, maintenance and remanufacturing costs of centers. The proposed model considers the design of a multi-layer, multi-product reverse supply chain that consists of returning, disassembly, processing, recycling, remanufacturing, materials and distribution centers. This integer linear programming model is solved by using Lingo 9 software and the results are reported. Finally, a sensitivity analysis of the proposed model is also presented.

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