Multicriteria inventory classification using a genetic algorithm

Cataloged from PDF version of article.One of the application areas of genetic algorithms is parameter optimization. This paper addresses the problem of optimizing a set of parameters that represent the weights of criteria, where the sum of all weights is 1. A chromosome represents the values of the weights, possibly along with some cut-off points. A new crossover operation, called continuous uniform crossover, is proposed, such that it produces valid chromosomes given that the parent chromosomes are valid. The new crossover technique is applied to the problem of multicriteria inventory classification. The results are compared with the classical inventory classification technique using the Analytical Hierarchy Process. @ 1998 Elsevier Science B.V

Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork

[EN] The need of organizations to ensure service levels that impact on customer satisfaction has required the design of collaborative processes among stakeholders involved in inventory decision making. The increase of quantity and variety of items, on the one hand, and demand and customer expectations, on the other hand, are transformed into a greater complexity in inventory management, requiring effective communication and agreements between the leaders of the logistics processes. Traditionally, decision making in inventory management was based on approaches conditioned only by cost or sales volume. These approaches must be overcome by others that consider multiple criteria, involving several areas of the companies and taking into account the opinions of the stakeholders involved in these decisions. Inventory management becomes part of a complex system that involves stakeholders from different areas of the company, where each agent has limited information and where the cooperation between such agents is key for the system's performance. In this paper, a distributed inventory control approach was used with the decisions allowing communication between the stakeholders and with a multicriteria group decision-making perspective. This work proposes a methodology that combines the analysis of the value chain and the AHP technique, in order to improve communication and the performance of the areas related to inventory management decision making. This methodology uses the areas of the value chain as a theoretical framework to identify the criteria necessary for the application of the AHP multicriteria group decision-making technique. These criteria were defined as indicators that measure the performance of the areas of the value chain related to inventory management and were used to classify ABC inventory of the products according to these selected criteria. Therefore, the methodology allows us to solve inventory management DDM based on multicriteria ABC classification and was validated in a Colombian company belonging to the graphic arts sector.Pérez Vergara, IG.; Arias Sánchez, JA.; Poveda Bautista, R.; Diego-Mas, JA. (2020). Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork. Complexity. 2020:1-13. https://doi.org/10.1155/2020/6758108S1132020Poveda-Bautista, R., Baptista, D. C., & García-Melón, M. (2012). Setting competitiveness indicators using BSC and ANP. International Journal of Production Research, 50(17), 4738-4752. doi:10.1080/00207543.2012.657964Castro Zuluaga, C. A., Velez Gallego, M. C., & Catro Urrego, J. A. (2011). 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Application of Artificial Neural Networks to Multiple Criteria Inventory Classification

Inventory classification is a very important part of inventory control which represents the technique of operational research discipline. A systematicapproach to the inventory control and classification may have a significant influence on company competitiveness. The paper describes the results obtained by investigating the application of neural networks in multiple criteria inventory classification. Various structures of a back-propagation neural network have been analysed and the optimal one with the minimum Root Mean Square error selected. The predicted results are compared to those obtained by the multiple criteria classification using the analytical hierarchy process

ABC Analysis For Inventory Management: Bridging The Gap Between Research And Classroom

ABC analysis is a well-established categorization technique based on the Pareto Principle for determining which items should get priority in the management of a company’s inventory.  In discussing this topic, today’s operations management and supply chain textbooks focus on dollar volume as the sole criterion for performing the categorization.  The authors argue that today’s businesses and supply chains operate in a world where the ability to deliver the right products rapidly to very specific markets is key to survival.  With suppliers, intermediaries, and customers all over the globe, and product lives decreasing rapidly, this focus on a single criterion is misplaced.  The large body of research was summarized based on multiple criteria ABC analysis that has accumulated since the 1980s and recommend that textbooks incorporate their key findings and methods into their discussions of this topic.  Suggestions are offered on how this discussion might be structured.

ABC Analysis For Inventory Management: Bridging The Gap Between Research And Classroom

ABC analysis is a well-established categorization technique based on the Pareto Principle for determining which items should get priority in the management of a company’s inventory.  In discussing this topic, today’s operations management and supply chain textbooks focus on dollar volume as the sole criterion for performing the categorization.  The authors argue that today’s businesses and supply chains operate in a world where the ability to deliver the right products rapidly to very specific markets is key to survival.  With suppliers, intermediaries, and customers all over the globe, and product lives decreasing rapidly, this focus on a single criterion is misplaced.  The large body of research was summarized based on multiple criteria ABC analysis that has accumulated since the 1980s and recommend that textbooks incorporate their key findings and methods into their discussions of this topic.  Suggestions are offered on how this discussion might be structured

ABC Analysis for Inventory Management: Bridging the Gap between Research and Classroom

ABC analysis is a well-established categorization technique based on the Pareto Principle for determining which items should get priority in the management of a company\u27s inventory. In discussing this topic, today\u27s operations management and supply chain textbooks focus on dollar volume as the sole criterion for performing the categorization. The authors argue that today\u27s businesses and supply chains operate in a world where the ability to deliver the right products rapidly to very specific markets is key to survival. With suppliers, intermediaries, and customers all over the globe, and product lives decreasing rapidly, this focus on a single criterion is misplaced. The large body of research was summarized based on multiple criteria ABC analysis that has accumulated since the 1980s and recommend that textbooks incorporate their key findings and methods into their discussions of this topic. Suggestions are offered on how this discussion might be structured

A comparison of multi-criteria methods for spare parts classification

Spare parts classification is a fundamental step in spare parts inventory management. Through classification, the parts are grouped using a set of relevant criteria. Methodologies and methods for multicriteria decision making are used to support the classification of spare parts. In this paper, a comparative study between the use of the multi-criteria classification based on rules and the multi-criteria classification using the Analytic Hierarchy Process is presented, showing the advantages and disadvantages of each method. The study confirmed that the multi-criteria method based on rules is more easily applied in organizations. The multi-criteria method using Analytic Hierarchy Process required more calculations, turning the implementation of the method more complicated, especially for non-Analytic Hierarchy Process specialists

Multicriteria hybrid flow shop scheduling problem: literature review, analysis, and future research

This research focuses on the Hybrid Flow Shop production scheduling problem, which is one of the most difficult problems to solve. The literature points to several studies that focus the Hybrid Flow Shop scheduling problem with monocriteria functions. Despite of the fact that, many real world problems involve several objective functions, they can often compete and conflict, leading researchers to concentrate direct their efforts on the development of methods that take consider this variant into consideration. The goal of the study is to review and analyze the methods in order to solve the Hybrid Flow Shop production scheduling problem with multicriteria functions in the literature. The analyses were performed using several papers that have been published over the years, also the parallel machines types, the approach used to develop solution methods, the type of method develop, the objective function, the performance criterion adopted, and the additional constraints considered. The results of the reviewing and analysis of 46 papers showed opportunities for future researchon this topic, including the following: (i) use uniform and dedicated parallel machines, (ii) use exact and metaheuristics approaches, (iv) develop lower and uppers bounds, relations of dominance and different search strategiesto improve the computational time of the exact methods,  (v) develop  other types of metaheuristic, (vi) work with anticipatory setups, and (vii) add constraints faced by the production systems itself

an evaluation methodology for the conversion of manual assembly systems into human robot collaborative workcells

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