A Hybrid Bacterial Swarming Methodology for Job Shop Scheduling Environment

Optimized utilization of resources is the need of the hour in any manufacturing system. A properly planned schedule is often required to facilitate optimization. This makes scheduling a significant phase in any manufacturing scenario. The Job Shop Scheduling Problem is an operation sequencing problem on multiple machines with some operation and machine precedence constraints, aimed to find the best sequence of operations on each machine in order to optimize a set of objectives. Bacterial Foraging algorithm is a relatively new biologically inspired optimization technique proposed based on the foraging behaviour of E.coli bacteria. Harmony Search is a phenomenon mimicking algorithm devised by the improvisation process of musicians. In this research paper, Harmony Search is hybridized with bacterial foraging to improve its scheduling strategies. A proposed Harmony Bacterial Swarming Algorithm is developed and tested with benchmark Job Shop instances. Computational results have clearly shown the competence of our method in obtaining the best schedule

Lot Streaming in Different Types of Production Processes: A PRISMA Systematic Review

At present, any industry that wanted to be considered a vanguard must be willing to improve itself, developing innovative techniques to generate a competitive advantage against its direct competitors. Hence, many methods are employed to optimize production processes, such as Lot Streaming, which consists of partitioning the productive lots into overlapping small batches to reduce the overall operating times known as Makespan, reducing the delivery time to the final customer. This work proposes carrying out a systematic review following the PRISMA methodology to the existing literature in indexed databases that demonstrates the application of Lot Streaming in the different production systems, giving the scientific community a strong consultation tool, useful to validate the different important elements in the definition of the Makespan reduction objectives and their applicability in the industry. Two hundred papers were identified on the subject of this study. After applying a group of eligibility criteria, 63 articles were analyzed, concluding that Lot Streaming can be applied in different types of industrial processes, always keeping the main objective of reducing Makespan, becoming an excellent improvement tool, thanks to the use of different optimization algorithms, attached to the reality of each industry.This work was supported by the Universidad Tecnica de Ambato (UTA) and their Research and Development Department (DIDE) under project CONIN-P-256-2019, and SENESCYT by grants “Convocatoria Abierta 2011” and “Convocatoria Abierta 2013”

Modelling and Scheduling Lot Streaming Flexible Flow Lines

Although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. This paper deals with scheduling jobs in lot streaming flexible flow line problems. The paper mathematically formulates the problem by a mixed integer linear programming model. This model solves small instances to optimality. Moreover, a novel artificial bee colony optimization is developed. This algorithm utilizes five effective mechanisms to solve the problem. To evaluate the algorithm, it is compared with adaptation of four available algorithms. The statistical analyses showed that the proposed algorithm significantly outperformed the other tested algorithms

KESİKLİ HARMONİ ARAMA ALGORİTMASI İLE OPTİMİZASYON PROBLEMLERİNİN ÇÖZÜMÜ: LİTERATÜR ARAŞTIRMASI

It is usually assumed the variables which are used in the optimization problems are continuous variables. However, the variables have discrete or integer values in many real life practices. Considering discrete integer variables in the optimization problems makes the problems more complex. There are few methods to solve these type of problems. The Harmony Search Algorithm inspired by improvisation of musical harmony and a recent variant of it, The Discrete Harmony Search Algorithm were investigated. It is thought that The usage of the Discrete Harmony Search Algorithm is going to provide a good alternative to solve the optimization problems.Genellikle optimizasyon problemlerinde kullanılan değişkenlerin sürekli değişkenler olduğu kabul edilmektedir. Ancak gerçek hayatta çoğu problemin değişkenleri kesikli veya tam sayı değişkenler şeklindedir. Optimizasyon problemlerinde kesikli tam sayı değişkenlerin dikkate alınmasıyla karmaşıklık daha fazla artmaktadır. Bu tür karmaşık problemlerin çözümünde az da olsa çeşitli yöntemler mevcuttur. Bu çalışmada bir müzik eserinde oluşan harmoniden esinlenilerek geliştirilen Harmoni Arama Algoritması ve henüz yeni bir uygulaması olan Kesikli Harmoni Arama Algoritması ile ilgili yapılan araştırmalar incelenmiştir. Kesikli Harmoni Arama Algoritması kullanılarak optimizasyon problemlerinin çözümü bu konuda bir alternatif sağlayacaktır

Adaptive and cooperative harmony search models for RNA secondary structure prediction

Penentuan fungsi molekul RNA amat bergantung kepada struktur sekundernya. Kaedah fizikal yang sedia ada untuk penentuan struktur sekunder adalah mahal dan memakan masa. Beberapa algoritma telah dicadangkan untuk peramalan struktur sekunder RNA, termasuk pengaturcaraan dinamik dan algoritma metaheuristik. Determining the function of RNA molecules relies heavily on its secondary structure. The current physical methods for secondary structure determination are expensive and time consuming. Several algorithms have been proposed for the RNA secondary structure prediction, including dynamic programming and metaheuristic algorithms

Adaptive And Cooperative Harmony Search Models For Rna Secondary Structure Prediction

Penentuan fungsi molekul RNA amat bergantung kepada struktur sekunderya. Kaedah fizikal yang sedia ada untuk penentuan struktur sekunder adalah mahal dan memakan masa. Determining the function of RNA molecules relies heavily on its secondary structure

Estado del arte de las aplicaciónes del concepto de Lot Streaming a la secuenciación en talleres de flujo

[ES] El presente estudio, versa en una revisión de los articulaos publicados sobre la aplicación del concepto de Lot Streaming y su aplicación en la secuenciación de talleres de flujo. Los documentos se clasificaron de acuerdo a los dimensionamientos que se asocian a evidenciar las combinaciones y comparaciones de diversos algoritmos utilizados para mejorar los talleres de flujo a través de la división de Sub-lotes. Lo cual representa un particular enfoque para la revisión de artículos e investigadores que han abordado esta temática, aplicando una metodología con un enfoque cualitativo, por cuanto la información se sistematizó a través del software Atlas_ti en correspondencia a las variables exploradas en cada estudio que identifican la eficacia de la división de lotes en la solución de problemas de talleres de flujo. La mayoría de los estudios identificaron algoritmos genéticos y genéticos híbridos, mostrando algunas desventajas frente a los tradicionales y en pocos estudios evidenciando la eficacia en su aplicación.[EN] The present study is based on a review of the articles published on the application of the Lot Streaming concept and its application in the sequencing of flow workshops. The documents were classified according to the sizing that is associated to evidence the combinations and comparisons of different algorithms used to improve the workshops of flow through the division of sublots. This represents a particular approach to the review of articles and researchers that have addressed this issue, applying a methodology with a qualitative approach, as the information is systematized through the Atlas_ti software in correspondence to the variables explored in each study that identify the efficiency of the division of batches in the solution of problems of flow workshops. The majority of the studies identified hybrid genetic and genetic algorithms, showing some disadvantages compared to the traditional ones and in few studies showing the efficacy in their application.Velecela Rojas, SJ. (2018). Estado del arte de las aplicaciónes del concepto de Lot Streaming a la secuenciación en talleres de flujo. http://hdl.handle.net/10251/110033TFG

Learning automata and sigma imperialist competitive algorithm for optimization of single and multi-objective functions

Evolutionary Algorithms (EA) consist of several heuristics which are able to solve optimisation tasks by imitating some aspects of natural evolution. Two widely-used EAs, namely Harmony Search (HS) and Imperialist Competitive Algorithm (ICA), are considered for improving single objective EA and Multi Objective EA (MOEA), respectively. HS is popular because of its speed and ICA has the ability for escaping local optima, which is an important criterion for a MOEA. In contrast, both algorithms have suffered some shortages. The HS algorithm could be trapped in local optima if its parameters are not tuned properly. This shortage causes low convergence rate and high computational time. In ICA, there is big obstacle that impedes ICA from becoming MOEA. ICA cannot be matched with crowded distance method which produces qualitative value for MOEAs, while ICA needs quantitative value to determine power of each solution. This research proposes a learnable EA, named learning automata harmony search (LAHS). The EA employs a learning automata (LA) based approach to ensure that HS parameters are learnable. This research also proposes a new MOEA based on ICA and Sigma method, named Sigma Imperialist Competitive Algorithm (SICA). Sigma method provides a mechanism to measure the solutions power based on their quantity value. The proposed LAHS and SICA algorithms are tested on wellknown single objective and multi objective benchmark, respectively. Both LAHS and MOICA show improvements in convergence rate and computational time in comparison to the well-known single EAs and MOEAs