Abstract
The aim of this study is the first evaluation of the Artificial Bee Colony Algorithm when applied to multi objective partial disassembly planning. Several methodologies have been proposed by academic and industrial researchers for developing and implementing automated disassembly planning and the research literature is very extensive. In particular, nature-inspired heuristic techniques seem to be very promising and performing well to optimize the disassembly planning problem, among them, the Artificial Bee Colony (ABC) approach, which has not yet been tested. The authors propose the implementation of a discrete ABC algorithm to plan the disassembly sequence of products, following these steps: matrix system modelling, multi-objective function and solution search with an ABC algorithm. In particular the study provides details of the algorithm and heuristic rules, inspired by the behaviour of bees during food search, which is a very efficient natural process. Two case studies have been selected and reported to test the efficiency of the algorithm, while further research is required to compare ABC to other efficient heuristics.
Highlights
In recent years, the concept of eco-efficiency has been developed, summarized in the expression “greater profit with lower impact”, achieving the aims of economic and environmental excellence
This study proposes a particular application of Artificial Bee Colony (ABC): Aimed to solve the problem of finding the optimal or sub-optimal disassembly sequence for an efficient planning process
The stability of the ABC approach for product disassembly planning must be further enhanced by studying a wider variety of product types and configurations
Summary
The concept of eco-efficiency has been developed, summarized in the expression “greater profit with lower impact”, achieving the aims of economic and environmental excellence. It is necessary to produce smaller quantities of waste and to reduce the use of raw materials, saving money and generating profits (Lee and Shih, 2012). In this context, disassembly tends to be costly, because of the increasing complexity and high variety of products. In this study a numerical approach to disassembly sequence planning is proposed, based on the optimization strategy of Artificial Bee Colony (ABC) whose power to search optimal assembly sequencing problems (Brajevic and Tuba, 2012; Akay and Karaboga, 2010) is known. Premature convergence can be an issue but in industrial applications, such as disassembly sequencing, suboptimal solution are normally taken into consideration as valid solutions
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Research Journal of Applied Sciences, Engineering and Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
