Multiobjective Optimization of Design and Manufacturing Tolerances Using TLBO Algorithm

Abstract

Tolerance design has become a very responsive and key issue in product and process development because of an informal compromise between functionality, quality, and manufacturing cost. The problem formulation becomes more complex with simultaneous selection of design and manufacturing tolerances and the optimization problem is difficult to solve with the traditional optimization techniques. Rao and More (Prod Manuf Res Open Access J 2: 71-94, 2014) used TLBO algorithm for the optimal selection of design and manufacturing tolerances with an alternative manufacturing process to obtain the optimal solution. An example of knuckle joint assembly with three arms is presented in this chapter and it is found that the TLBO algorithm has produced better results when compared to those obtained using NSGA-II and MOPSO algorithms.

Dynamic placement of virtual machines using an improved multi‐objective teaching‐learning based optimization algorithm in cloud

“…Therefore, reducing energy consumption in CDCs is an important challenge 6 . Recent studies have shown that energy consumption by PSs has a linear relationship with processor utilization 7 . Proper migration of VMs between PSs can reduce energy consumption and violating the service level agreement (SLA) in CDCs 3,6,7 .…”

“…Consolidating PSs using virtualization technology is widely used to reduce energy consumption in CDCs. In this regard, VMs placement (VMP) plays an important role in PSs consolidation technology 7 …”

“…Previous works in the field of VMP has different objectives in problem solving 6 . Some algorithms determine the appropriate PS for deploying VMs in order to reduce energy consumption 7 . Some previous work has used multi‐objective optimization solutions to solve the VMP problem 8 .…”

“…VMP is an NP‐hard problem that complicates the issue of power management in CDCs 6 . VMP problem‐solving approaches use VMs resource information to minimize the number of active PSs in order to reduce energy consumption 3,6,7 …”

“…Recently, meta‐heuristic approaches to VMP problem solving are very popular 7 . Rao 7 used the classical teaching learning based optimization (TLBO) algorithm to optimally select resources in CDCs to achieve the optimal solution.…”