Multi-objective optimisation of tool indexing problem: a mathematical model and a modified genetic algorithm

Machining process efficiencies can be improved by minimising the non-machining time, thereby resulting in short operation cycles. In automatic-machining centres, this is realised via optimum cutting tool allocation on turret-magazine indices – “tool-indexing problem”. Extant literature simplifies TIP as a single-objective optimisation problem considering minimisation of only tool-indexing time. contrast, study aims to address multi-objective (MOOTIP) identifying changes that must made current industrial settings an additional objective. Furthermore, duplicates and lifespan have been considered. addition, novel mathematical model proposed for solving MOOTIP. Given complexity problem, authors suggest use modified strength Pareto evolutionary algorithm combined with customised environment-selection mechanism. The approach attained uniform distribution solutions realise above objectives. Additionally, solution representation was developed along corresponding genetic operators ensure feasibility obtained. Results obtained demonstrate realization not significant (70%) reduction time but also set tradeoff decision makers manage their tools more efficiently compared practices.