Vendor managed inventory is a continuous replenishment program that is designed to provide major cost saving benefits for both vendors and retailers. Previous research on this area mainly included single objective optimization models where the objective is to minimize the total supply chain costs or to maximize the total supply chain benefits. This paper presents a bi-objective mathematical mod...

the present paper aims to investigate the effects of modularity and the layout of subsystems and parts of a complex system on its maintainability. for this purpose, four objective functions have been considered simultaneously: i) maximizing the level of accordance between system design and optimum modularity design,ii) maximizing the level of accessibility and the maintenance space required,iii...

With respect to the two-sided matching problem, where the agents’ preferences are in the format of multi-granularity uncertain linguistic terms, a matching method is proposed. Some basic concepts and definitions on uncertain linguistic term and 2-tuple are firstly given. Based on this, the two-sided matching problem with multi-granularity uncertain linguistic terms is described. Then, multi-gra...

This paper presents a strategy based on fuzzy logic and lexicographic multi-objective optimization for designing noise abatement procedures aimed at reducing the noise exposure of the population living around the airports. A non-linear multi-objective optimal control problem is formally written and identified. A lexicographic optimization technique is presented for establishing a hierarchical o...

In this paper, a multi-objective constrained optimization model is proposed to improve interpretability of TSK fuzzy models. This approach allows a linguistic approximation of the fuzzy models. Three different multi-objective evolutionary algorithms (MONEA, ENORA and NSGA-II) are used together with neural network techniques. These algorithms are checked out in the approximation of a dynamic non...

The design of linear Support Vector Machine (SVM) classification techniques is generally a Multi-objective Optimization Problem (MOP). These require finding appropriate trade-offs between two objectives, such as the amount misclassified training data (classification error) and number non-zero elements separator hyperplane. In this article, we review several SVM models in form multi-objective op...

Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier‎. ‎This paper applies an evolutionary optimization scheme‎, ‎inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...