32,119 research outputs found

    Facility layout problem: Bibliometric and benchmarking analysis

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    Facility layout problem is related to the location of departments in a facility area, with the aim of determining the most effective configuration. Researches based on different approaches have been published in the last six decades and, to prove the effectiveness of the results obtained, several instances have been developed. This paper presents a general overview on the extant literature on facility layout problems in order to identify the main research trends and propose future research questions. Firstly, in order to give the reader an overview of the literature, a bibliometric analysis is presented. Then, a clusterization of the papers referred to the main instances reported in literature was carried out in order to create a database that can be a useful tool in the benchmarking procedure for researchers that would approach this kind of problems

    Overview of Dynamic Facility Layout Planning as a Sustainability Strategy

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    [EN] The facility layout design problem is significantly relevant within the business operations strategies framework and has emerged as an alternate strategy towards supply chain sustainability. However, its wide coverage in the scientific literature has focused mainly on the static planning approach and disregarded the dynamic approach, which is very useful in real-world applications. In this context, the present article offers a literature review of the dynamic facility layout problem (DFLP). First, a taxonomy of the reviewed papers is proposed based on the problem formulation current trends (related to the problem type, planning phase, planning approach, number of facilities, number of floors, number of departments, space consideration, department shape, department dimensions, department area, and materials handling configuration); the mathematical modeling approach (regarding the type of model, type of objective function, type of constraints, nature of market demand, type of data, and distance metric), and the considered solution approach. Then, the extent to which recent research into DFLP has contributed to supply chain sustainability by addressing its three performance dimensions (economic, environmental, social) is described. Finally, some future research guidelines are provided.This research was funded by the Spanish Ministry of Science, Innovation and Universities Project CADS4.0, grant number RTI2018-101344-B-I00; and the Valencian Community ERDF Programme 2014-2020, grant number IDIFEDER/2018/025.PĂ©rez-Gosende, P.; Mula, J.; DĂ­az-Madroñero Boluda, FM. (2020). Overview of Dynamic Facility Layout Planning as a Sustainability Strategy. Sustainability. 12(19):1-16. https://doi.org/10.3390/su12198277S1161219Ghassemi Tari, F., & Neghabi, H. (2015). A new linear adjacency approach for facility layout problem with unequal area departments. Journal of Manufacturing Systems, 37, 93-103. doi:10.1016/j.jmsy.2015.09.003Kheirkhah, A., Navidi, H., & Messi Bidgoli, M. (2015). Dynamic Facility Layout Problem: A New Bilevel Formulation and Some Metaheuristic Solution Methods. IEEE Transactions on Engineering Management, 62(3), 396-410. doi:10.1109/tem.2015.2437195Altuntas, S., & Selim, H. (2012). Facility layout using weighted association rule-based data mining algorithms: Evaluation with simulation. Expert Systems with Applications, 39(1), 3-13. doi:10.1016/j.eswa.2011.06.045Ku, M.-Y., Hu, M. H., & Wang, M.-J. (2011). Simulated annealing based parallel genetic algorithm for facility layout problem. International Journal of Production Research, 49(6), 1801-1812. doi:10.1080/00207541003645789Navidi, H., Bashiri, M., & Messi Bidgoli, M. (2012). A heuristic approach on the facility layout problem based on game theory. International Journal of Production Research, 50(6), 1512-1527. doi:10.1080/00207543.2010.550638Hosseini-Nasab, H., Fereidouni, S., Fatemi Ghomi, S. M. T., & Fakhrzad, M. B. (2017). Classification of facility layout problems: a review study. The International Journal of Advanced Manufacturing Technology, 94(1-4), 957-977. doi:10.1007/s00170-017-0895-8Carter, C. R., & Rogers, D. S. (2008). A framework of sustainable supply chain management: moving toward new theory. International Journal of Physical Distribution & Logistics Management, 38(5), 360-387. doi:10.1108/09600030810882816Carter, C. R., & Washispack, S. (2018). Mapping the Path Forward for Sustainable Supply Chain Management: A Review of Reviews. Journal of Business Logistics, 39(4), 242-247. doi:10.1111/jbl.12196Roy, V., Schoenherr, T., & Charan, P. (2018). The thematic landscape of literature in sustainable supply chain management (SSCM). International Journal of Operations & Production Management, 38(4), 1091-1124. doi:10.1108/ijopm-05-2017-0260Barbosa-PĂłvoa, A. P., da Silva, C., & Carvalho, A. (2018). Opportunities and challenges in sustainable supply chain: An operations research perspective. European Journal of Operational Research, 268(2), 399-431. doi:10.1016/j.ejor.2017.10.036Tonelli, F., Evans, S., & Taticchi, P. (2013). Industrial sustainability: challenges, perspectives, actions. International Journal of Business Innovation and Research, 7(2), 143. doi:10.1504/ijbir.2013.052576SĂĄnchez-Flores, R. B., Cruz-Sotelo, S. E., Ojeda-Benitez, S., & RamĂ­rez-Barreto, M. E. (2020). Sustainable Supply Chain Management—A Literature Review on Emerging Economies. Sustainability, 12(17), 6972. doi:10.3390/su12176972Ford, S., & Despeisse, M. (2016). Additive manufacturing and sustainability: an exploratory study of the advantages and challenges. Journal of Cleaner Production, 137, 1573-1587. doi:10.1016/j.jclepro.2016.04.150Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, 117, 408-425. doi:10.1016/j.psep.2018.05.009Khuntia, J., Saldanha, T. J. V., Mithas, S., & Sambamurthy, V. (2018). Information Technology and Sustainability: Evidence from an Emerging Economy. Production and Operations Management, 27(4), 756-773. doi:10.1111/poms.12822Roy, S., Das, M., Ali, S. M., Raihan, A. S., Paul, S. K., & Kabir, G. (2020). Evaluating strategies for environmental sustainability in a supply chain of an emerging economy. Journal of Cleaner Production, 262, 121389. doi:10.1016/j.jclepro.2020.121389Morais, D. O. C., & Silvestre, B. S. (2018). Advancing social sustainability in supply chain management: Lessons from multiple case studies in an emerging economy. Journal of Cleaner Production, 199, 222-235. doi:10.1016/j.jclepro.2018.07.097Stindt, D. (2017). A generic planning approach for sustainable supply chain management - How to integrate concepts and methods to address the issues of sustainability? Journal of Cleaner Production, 153, 146-163. doi:10.1016/j.jclepro.2017.03.126MOSLEMIPOUR, G., LEE, T. S., & LOONG, Y. T. (2017). Performance Analysis of Intelligent Robust Facility Layout Design. Chinese Journal of Mechanical Engineering, 30(2), 407-418. doi:10.1007/s10033-017-0073-9Emami, S., & S. Nookabadi, A. (2013). Managing a new multi-objective model for the dynamic facility layout problem. The International Journal of Advanced Manufacturing Technology, 68(9-12), 2215-2228. doi:10.1007/s00170-013-4820-5Al Hawarneh, A., Bendak, S., & Ghanim, F. (2019). Dynamic facilities planning model for large scale construction projects. Automation in Construction, 98, 72-89. doi:10.1016/j.autcon.2018.11.021Pournaderi, N., Ghezavati, V. R., & Mozafari, M. (2019). Developing a mathematical model for the dynamic facility layout problem considering material handling system and optimizing it using cloud theory-based simulated annealing algorithm. SN Applied Sciences, 1(8). doi:10.1007/s42452-019-0865-xTuranoğlu, B., & Akkaya, G. (2018). A new hybrid heuristic algorithm based on bacterial foraging optimization for the dynamic facility layout problem. Expert Systems with Applications, 98, 93-104. doi:10.1016/j.eswa.2018.01.011Moslemipour, G., Lee, T. S., & Rilling, D. (2011). A review of intelligent approaches for designing dynamic and robust layouts in flexible manufacturing systems. The International Journal of Advanced Manufacturing Technology, 60(1-4), 11-27. doi:10.1007/s00170-011-3614-xTebaldi, L., Bigliardi, B., & Bottani, E. (2018). Sustainable Supply Chain and Innovation: A Review of the Recent Literature. Sustainability, 10(11), 3946. doi:10.3390/su10113946Tseng, M.-L., Islam, M. S., Karia, N., Fauzi, F. A., & Afrin, S. (2019). A literature review on green supply chain management: Trends and future challenges. Resources, Conservation and Recycling, 141, 145-162. doi:10.1016/j.resconrec.2018.10.009Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869. doi:10.1016/j.jclepro.2019.119869Boar, A., Bastida, R., & Marimon, F. (2020). A Systematic Literature Review. Relationships between the Sharing Economy, Sustainability and Sustainable Development Goals. Sustainability, 12(17), 6744. doi:10.3390/su12176744Novais, L., Maqueira, J. M., & Ortiz-Bas, Á. (2019). A systematic literature review of cloud computing use in supply chain integration. Computers & Industrial Engineering, 129, 296-314. doi:10.1016/j.cie.2019.01.056Masi, D., Day, S., & Godsell, J. (2017). Supply Chain Configurations in the Circular Economy: A Systematic Literature Review. Sustainability, 9(9), 1602. doi:10.3390/su9091602Zavala-AlcĂ­var, A., Verdecho, M.-J., & Alfaro-Saiz, J.-J. (2020). A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain. Sustainability, 12(16), 6300. doi:10.3390/su12166300Li, K., Rollins, J., & Yan, E. (2017). Web of Science use in published research and review papers 1997–2017: a selective, dynamic, cross-domain, content-based analysis. Scientometrics, 115(1), 1-20. doi:10.1007/s11192-017-2622-5Kulturel-Konak, S., & Konak, A. (2014). A large-scale hybrid simulated annealing algorithm for cyclic facility layout problems. Engineering Optimization, 47(7), 963-978. doi:10.1080/0305215x.2014.933825Madhusudanan Pillai, V., Hunagund, I. B., & Krishnan, K. K. (2011). Design of robust layout for Dynamic Plant Layout Problems. Computers & Industrial Engineering, 61(3), 813-823. doi:10.1016/j.cie.2011.05.014Peng, Y., Zeng, T., Fan, L., Han, Y., & Xia, B. (2018). An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem. Discrete Dynamics in Nature and Society, 2018, 1-8. doi:10.1155/2018/1529058McKendall, A. R., & Hakobyan, A. (2010). Heuristics for the dynamic facility layout problem with unequal-area departments. European Journal of Operational Research, 201(1), 171-182. doi:10.1016/j.ejor.2009.02.028Yang, C.-L., Chuang, S.-P., & Hsu, T.-S. (2010). A genetic algorithm for dynamic facility planning in job shop manufacturing. The International Journal of Advanced Manufacturing Technology, 52(1-4), 303-309. doi:10.1007/s00170-010-2733-0Abedzadeh, M., Mazinani, M., Moradinasab, N., & Roghanian, E. (2012). Parallel variable neighborhood search for solving fuzzy multi-objective dynamic facility layout problem. The International Journal of Advanced Manufacturing Technology, 65(1-4), 197-211. doi:10.1007/s00170-012-4160-xGuan, X., Dai, X., Qiu, B., & Li, J. (2012). A revised electromagnetism-like mechanism for layout design of reconfigurable manufacturing system. Computers & Industrial Engineering, 63(1), 98-108. doi:10.1016/j.cie.2012.01.016Jolai, F., Tavakkoli-Moghaddam, R., & Taghipour, M. (2012). A multi-objective particle swarm optimisation algorithm for unequal sized dynamic facility layout problem with pickup/drop-off locations. International Journal of Production Research, 50(15), 4279-4293. doi:10.1080/00207543.2011.613863Kia, R., Baboli, A., Javadian, N., Tavakkoli-Moghaddam, R., Kazemi, M., & Khorrami, J. (2012). Solving a group layout design model of a dynamic cellular manufacturing system with alternative process routings, lot splitting and flexible reconfiguration by simulated annealing. Computers & Operations Research, 39(11), 2642-2658. doi:10.1016/j.cor.2012.01.012McKendall, A. R., & Liu, W.-H. (2012). New Tabu search heuristics for the dynamic facility layout problem. International Journal of Production Research, 50(3), 867-878. doi:10.1080/00207543.2010.545446Hosseini-Nasab, H., & Emami, L. (2013). A hybrid particle swarm optimisation for dynamic facility layout problem. International Journal of Production Research, 51(14), 4325-4335. doi:10.1080/00207543.2013.774486Kaveh, M., Dalfard, V. M., & Amiri, S. (2013). A new intelligent algorithm for dynamic facility layout problem in state of fuzzy constraints. Neural Computing and Applications, 24(5), 1179-1190. doi:10.1007/s00521-013-1339-5KIA, R., JAVADIAN, N., PAYDAR, M. M., & SAIDI-MEHRABAD, M. (2013). A SIMULATED ANNEALING FOR INTRA-CELL LAYOUT DESIGN OF DYNAMIC CELLULAR MANUFACTURING SYSTEMS WITH ROUTE SELECTION, PURCHASING MACHINES AND CELL RECONFIGURATION. Asia-Pacific Journal of Operational Research, 30(04), 1350004. doi:10.1142/s0217595913500048Mazinani, M., Abedzadeh, M., & Mohebali, N. (2012). Dynamic facility layout problem based on flexible bay structure and solving by genetic algorithm. The International Journal of Advanced Manufacturing Technology, 65(5-8), 929-943. doi:10.1007/s00170-012-4229-6Samarghandi, H., Taabayan, P., & Behroozi, M. (2013). Metaheuristics for fuzzy dynamic facility layout problem with unequal area constraints and closeness ratings. The International Journal of Advanced Manufacturing Technology, 67(9-12), 2701-2715. doi:10.1007/s00170-012-4685-zYu-Hsin Chen, G. (2013). A new data structure of solution representation in hybrid ant colony optimization for large dynamic facility layout problems. International Journal of Production Economics, 142(2), 362-371. doi:10.1016/j.ijpe.2012.12.012Bozorgi, N., Abedzadeh, M., & Zeinali, M. (2014). Tabu search heuristic for efficiency of dynamic facility layout problem. The International Journal of Advanced Manufacturing Technology, 77(1-4), 689-703. doi:10.1007/s00170-014-6460-9CHEN, G. Y.-H., & LO, J.-C. (2014). DYNAMIC FACILITY LAYOUT WITH MULTI-OBJECTIVES. Asia-Pacific Journal of Operational Research, 31(04), 1450027. doi:10.1142/s0217595914500274Hosseini, S., Khaled, A. A., & Vadlamani, S. (2014). Hybrid imperialist competitive algorithm, variable neighborhood search, and simulated annealing for dynamic facility layout problem. Neural Computing and Applications, 25(7-8), 1871-1885. doi:10.1007/s00521-014-1678-xKia, R., Khaksar-Haghani, F., Javadian, N., & Tavakkoli-Moghaddam, R. (2014). Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm. Journal of Manufacturing Systems, 33(1), 218-232. doi:10.1016/j.jmsy.2013.12.005Nematian, J. (2014). A robust single row facility layout problem with fuzzy random variables. The International Journal of Advanced Manufacturing Technology, 72(1-4), 255-267. doi:10.1007/s00170-013-5564-yPourvaziri, H., & Naderi, B. (2014). A hybrid multi-population genetic algorithm for the dynamic facility layout problem. Applied Soft Computing, 24, 457-469. doi:10.1016/j.asoc.2014.06.051Derakhshan Asl, A., & Wong, K. Y. (2015). Solving unequal-area static and dynamic facility layout problems using modified particle swarm optimization. Journal of Intelligent Manufacturing, 28(6), 1317-1336. doi:10.1007/s10845-015-1053-5Li, L., Li, C., Ma, H., & Tang, Y. (2015). An Optimization Method for the Remanufacturing Dynamic Facility Layout Problem with Uncertainties. Discrete Dynamics in Nature and Society, 2015, 1-11. doi:10.1155/2015/685408Ulutas, B., & Islier, A. A. (2015). Dynamic facility layout problem in footwear industry. Journal of Manufacturing Systems, 36, 55-61. doi:10.1016/j.jmsy.2015.03.004Zarea Fazlelahi, F., Pournader, M., Gharakhani, M., & Sadjadi, S. J. (2016). A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 230(12), 2264-2274. doi:10.1177/0954405415615728Hosseini, S. S., & Seifbarghy, M. (2016). A novel meta-heuristic algorithm for multi-objective dynamic facility layout problem. RAIRO - Operations Research, 50(4-5), 869-890. doi:10.1051/ro/2016057Pourvaziri, H., & Pierreval, H. (2017). Dynamic facility layout problem based on open queuing network theory. European Journal of Operational Research, 259(2), 538-553. doi:10.1016/j.ejor.2016.11.011Tayal, A., & Singh, S. P. (2016). Integrating big data analytic and hybrid firefly-chaotic simulated annealing approach for facility layout problem. Annals of Operations Research, 270(1-2), 489-514. doi:10.1007/s10479-016-2237-xKumar, R., & Singh, S. P. (2017). A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems. Engineering Optimization, 49(11), 1848-1867. doi:10.1080/0305215x.2016.1274205Liu, J., Wang, D., He, K., & Xue, Y. (2017). Combining Wang–Landau sampling algorithm and heuristics for solving the unequal-area dynamic facility layout problem. European Journal of Operational Research, 262(3), 1052-1063. doi:10.1016/j.ejor.2017.04.002Vitayasak, S., Pongcharoen, P., & Hicks, C. (2017). A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic Algorithm or modified Backtracking Search Algorithm. International Journal of Production Economics, 190, 146-157. doi:10.1016/j.ijpe.2016.03.019Xiao, Y., Xie, Y., Kulturel-Konak, S., & Konak, A. (2017). A problem evolution algorithm with linear programming for the dynamic facility layout problem—A general layout formulation. Computers & Operations Research, 88, 187-207. doi:10.1016/j.cor.2017.06.025Li, J., Tan, X., & Li, J. (2018). Research on Dynamic Facility Layout Problem of Manufacturing Unit Considering Human Factors. Mathematical Problems in Engineering, 2018, 1-13. doi:10.1155/2018/6040561Vitayasak, S., & Pongcharoen, P. (2018). Performance improvement of Teaching-Learning-Based Optimisation for robust machine layout design. Expert Systems with Applications, 98, 129-152. doi:10.1016/j.eswa.2018.01.005Wei, X., Yuan, S., & Ye, Y. (2019). Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm. Production & Manufacturing Research, 7(1), 109-124. doi:10.1080/21693277.2019.1602486Kulturel-Konak, S. (2007). Approaches to uncertainties in facility layout problems: Perspectives at the beginning of the 21st Century. Journal of Intelligent Manufacturing, 18(2), 273-284. doi:10.1007/s10845-007-0020-1Sharma, P., & Singhal, S. (2016). Implementation of fuzzy TOPSIS methodology in selection of procedural approach for facility layout planning. The International Journal of Advanced Manufacturing Technology, 88(5-8), 1485-1493. doi:10.1007/s00170-016-8878-8Bukchin, Y., & Tzur, M. (2014). A new MILP approach for the facility process-layout design problem with rectangular and L/T shape departments. 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    The single row layout problem with clearances

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    The single row layout problem (SRLP) is a specially structured instance of the classical facility layout problem, especially used in flexible manufacturing systems. The SRLP consists of finding the most efficient arrangement of a given number of machines along one side of the material handling path with the purpose of minimising the total weighted sum of distances among all machine pairs. To reflect real manufacturing situations, a minimum space (so-called clearances) between machines may be required by observing technological constraints, safety considerations and regulations. This thesis intends to outline the different concepts of clearances used in literature and analyse their effects on modelling and solution approaches for the SRLP. In particular the special characteristics of sequence-dependent, asymmetric clearances are discussed and finally extended to large size clearances (machine-spanning clearances). For this, adjusted and novel model formulations and solution approaches are presented. Furthermore, a comprehensive survey of articles published in this research area since 2000 is provided which identify recent developments and emerging trends in SRLP

    Facility layout planning. An extended literature review

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    [EN] Facility layout planning (FLP) involves a set of design problems related to the arrangement of the elements that shape industrial production systems in a physical space. The fact that they are considered one of the most important design decisions as part of business operation strategies, and their proven repercussion on production systems' operation costs, efficiency and productivity, mean that this theme has been widely addressed in science. In this context, the present article offers a scientific literature review about FLP from the operations management perspective. The 232 reviewed articles were classified as a large taxonomy based on type of problem, approach and planning stage and characteristics of production facilities by configuring the material handling system and methods to generate and assess layout alternatives. We stress that the generation of layout alternatives was done mainly using mathematical optimisation models, specifically discrete quadratic programming models for similar sized departments, or continuous linear and non-linear mixed integer programming models for different sized departments. Other approaches followed to generate layout alternatives were expert's knowledge and specialised software packages. Generally speaking, the most frequent solution algorithms were metaheuristics.The research leading to these results received funding from the European Union H2020 Program under grant agreement No 958205 `Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)'and from the Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-101344-B-I00 `Optimisation of zerodefectsproduction technologies enabling supply chains 4.0 (CADS4.0)'Pérez-Gosende, P.; Mula, J.; Díaz-Madroñero Boluda, FM. (2021). Facility layout planning. An extended literature review. International Journal of Production Research. 59(12):3777-3816. https://doi.org/10.1080/00207543.2021.189717637773816591

    Multi-objective optimization in single-row layout design using a genetic algorithm

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    This paper presents the development of a genetic algorithm for determining a common linear machine sequence for multi-products with different operation sequences and facilities with a limited number of duplicate machine types available for a job. This work aims to minimize the total flow distance travelled by products, reduce the number of machines arranged in the final linear sequence, and decrease the total investment cost of the machines used in the final sequence. We assume that product flow runs only in the forward direction, either via in-sequence or bypass movement. We demonstrate the effectiveness of the proposed algorithm by solving a typical layout design problem taken from literature, and several randomly generated problems. Results indicate that the proposed algorithm serves as a practical decision support tool for resolving layout problems in manufacturing facilities

    A simple heuristic for linear sequencing of machines in layout design

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    This paper presents a simple heuristic to determine a common linear machine sequence for multiple products with different operation sequences and a limited number of duplicate machine types available for the job. The heuristic is based on minimisation of the total flow distance travelled by a product on the linear machine sequence. It is assumed that the flows of products are allowed only in the forward direction, either in-sequence or by-pass. It is also assumed that backtrack movements are not allowed. The effectiveness of the proposed heuristic is demonstrated through the solutions of two typical layout design problems taken from the literature. Subsequently, a number of additional problems are solved and their results are compared with the results applying existing methods. The results indicate that the proposed method can be an effective tool in solving layout design problems

    Tabu Search for the Single Row Facility Layout Problem in FMS using a 3-opt Neighborhood

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    Since material handling agents in a FMS are most efficient when moving in straight lines, a common layout of machines in a FMS is a single row layout. This allows a floor designer to model the problem of generating an optimal machine layout in a FMS as a single row facility layout problem (SRFLP). Due to the computational complexity involved in solving the SRFLP, researchers have developed several heuristics to solve large instances of the problem. In this paper, we present a tabu search implementation based on a 3-opt neighborhood search scheme. We also present a technique to speed up the exhaustive 3-opt neighborhood search process significantly. Our computational experiments show that speed up of the 3-opt search is effective, and our tabu search implementation is competitive. The results we present here are better than the currently known best layouts for several large sized benchmark SRFLP instances, and competitive for other benchmark instances.

    Facility Planning and Associated Problems: A Survey

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    In this study, we have classified and reviewed different types of problems which are related to facility planning and layout design for different types of manufacturing processes. The main problems which are related to location of  facilities which also affects the system performance  such as distribution of man, material and machine in a plant or a factory and their optimization technique while using of mathematical models, their solutions and application related to whole problems is presented. For solving this type of problems, intelligent techniques such as expert systems, fuzzy logic and neutral networks have been used. In this paper the recent analysis on facility layout is incorporated and facility layout problem is surveyed. Many intelligent techniques and conventional algorithms for solving FLP are presented. In our discussion different research direction, general remarks and tendencies have been mentioned Keywords—Facility Planning, Material handling Optimization metho

    FirstLight: Pluggable Optical Interconnect Technologies for Polymeric Electro-Optical Printed Circuit Boards in Data Centers

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    The protocol data rate governing data storage devices will increase to over 12 Gb/s by 2013 thereby imposing unmanageable cost and performance burdens on future digital data storage systems. The resulting performance bottleneck can be substantially reduced by conveying high-speed data optically instead of electronically. A novel active pluggable 82.5 Gb/s aggregate bit rate optical connector technology, the design and fabrication of a compact electro-optical printed circuit board to meet exacting specifications, and a method for low cost, high precision, passive optical assembly are presented. A demonstration platform was constructed to assess the viability of embedded electro-optical midplane technology in such systems including the first ever demonstration of a pluggable active optical waveguide printed circuit board connector. High-speed optical data transfer at 10.3125 Gb/s was demonstrated through a complex polymer waveguide interconnect layer embedded into a 262 mm × 240 mm × 4.3 mm electro-optical midplane. Bit error rates of less than 10-12 and optical losses as low as 6 dB were demonstrated through nine multimode polymer wave guides with an aggregate data bandwidth of 92.8125 Gb/s

    Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms

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    The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA) methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels. The first level of hybridization consists of the development of a Fuzzy controller for the parameters of an assembly or disassembly planner based on GAs. This controller acts on mutation probability and crossover rate in order to adapt their values dynamically while the algorithm runs. The second level consists of the identification of theoptimal assembly or disassembly sequence by a Fuzzy function, in order to obtain a closer control of the technological knowledge of the assembly/disassembly process. Two case studies were analyzed in order to test the efficiency of the Fuzzy-GA methodologies
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