Operation Sequencing Optimization in CAPP Using Hybrid Teaching-Learning Based Optimization (HTLBO)

Subject Areas : Tectonostratigraphy

Hassan  Halleh ¹ (Golpayegan University of Technology, Golpayegan, Iran)
Azam  Sadati ² (Islamic Azad University, Khomein Branch, Khomein, Iran)
Nasser  Hajisharifi ³ (Department of mathematics, Collage of basic sciences, Islamic azad university, Khomein branch, Khomein, Iran)

Received: 2014-10-18 Accepted : 2019-07-16 Published : 2020-06-01

Keywords: Computer-aided process planning (CAPP), Operation sequence, Hamilton path, Teaching–learning-based optimization,

Abstract :

Computer-aided process planning (CAPP) is an essential component in linking computer-aided design (CAD) and computer-aided manufacturing (CAM). Operation sequencing in CAPP is an essential activity. Each sequence of production operations which is produced in a process plan cannot be the best possible sequence every time in a changing production environment. As the complexity of the product increases, the number of feasible sequences increase exponentially, consequently the best sequence is to be chosen. This paper aims at presenting the application of a newly developed meta-heuristic called the hybrid teaching–learning-based optimization (HTLBO) as a global search technique for the quick identification of the optimal sequence of operations with consideration of various feasibility constraints. To do so, three case studies have been conducted to evaluate the performance of the proposed algorithm and a comparison between the proposed algorithm and the previous searches from the literature has been made. The results show that HTLBO performs well in operation sequencing problem.

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