Vendor selection decisions are complicated by the fact that various conflicting multi-objective factors must be considered in the decision making process. The problem of vendor selection becomes still more compli-cated with the inclusion of incremental discount pricing schedule. Such hard combinatorial problems when solved using meta heuristics produce near optimal solutions. This paper propose...

Empirical research suggests that most corporate consumer affairs departments are not a part of the decision-making structure of their respective firms. The typical consumer affairs department appears to have little influence in management decisions that affect consumer satisfaction and welfare. As a result, it is of limited value for the consumer. A reason for the isolation of consumer affairs ...

This paper will address an innovative bio-inspired algorithm able to incrementally grow decision graphs in multiple directions for discrete multi-objective optimisation. The algorithm takes inspiration from the slime mould Physarum Polycephalum, an amoeboid organism that in its plasmodium state extends and optimizes a net of veins looking for food. The algorithm is here used to solve multi-obje...

This paper proposes an integrated approach to arrive at optimal build orientations, simultaneously minimizing surface roughness ’Ra’ and build time ’T ’, for object manufacturing in SLS process. The optimization task is carried out by two popularly known multi-objective evolutionary optimizers NSGA-II (non-dominated sorting genetic algorithm) and MOPSO (multi-objective particle swarm optimizer)...

In this paper, we describe a systematic multi-objective problem solving approach, simulataneosly minimizing two conflicting goals average surface roughness ‘Ra’ and build time ‘T ’, for object manufacturing in FDM process by usage of evolutionary algorithms. Popularly used multi-objective genetic algorithm NSGA-II and recently proposed multi-objective particle swarm optimization (MOPSO) algorit...

Flatness is a vital quality index that determines the dimensional accuracy of cold-rolled strip. This paper designs local shape wave extraction algorithm and fuzzy classification for overall flatness defect based on cosine distance. By introducing small displacement buckling theory thin plates, plate stress model waves studied, critical elongation difference under given conditions are obtained....

Decision Neural Network is a new approach for solving multi-objective decision-making problems based on artificial neural networks. Using inaccurate evaluation data, network training has improved and the number of educational data sets has decreased. The available training method is based on the gradient decent method (BP). One of its limitations is related to its convergence speed. Therefore,...