Multi-objective optimization (MO) has been an active area of research in the last two decades. In multi-objective genetic algorithm (MOGA), the quality of newly generated offspring of the population will directly affect the performance of finding the Pareto optimum. In this paper, an improved MOGA, named SMGA, is proposed for solving multi-objective optimization problems. To increase efficiency...

Vehicle suspension design must fulfill some conflicting criteria. Among those is ride comfort which is attained by minimizing the acceleration transmitted to the sprung mass, via suspension spring and damper. Also good handling of a vehicle is a desirable property which requires stiff suspension and therefore is in contrast with a vehicle with good ride. Among the other desirable features of a ...

this paper is a research on the ordering planning of a supply chain with one supplier, multi buyer and multi deteriorating items. items have fixed life time and expire dates. the ordering period is taken as variable and must be computed the proposed models. the problem is studied via two different approaches the first is the joint replenishment, based on the hwang and chew's model [3] and ...

We propose a general framework for support vector machines (SVM) based on the principle of multi-objective optimization. The learning of SVMs is formulated as a multiobjective program by setting two competing goals to minimize the empirical risk and minimize the model capacity. Distinct approaches to solving the MOP introduce various SVM formulations. The proposed framework enables a more effec...

The convexity theory plays an important role in many aspects of mathematical programming. In recent years, in order to relax convexity assumption, various generalized convexity notions have been obtained. One of them is the concept of ) , ( r p B− invexity defined by T.Antczak [1], which extended the class of B − invex functions with respect toη and b and the classes of ) , ( r p invex function...

data envelopment analysis operates as a tool for appraising the relative efficiency of a set of homogenous decision making units. this methodology is applied widely in different contexts. regarding to its logic, dea allows each dmu to take its optimal weight in comparison with other dmus while a similar condition is considered for other units. this feature is a bilabial characteristic which opt...

since the 1990’s, network reliability has been considered as a new index for evaluating transportation networks under uncertainty. a large number of studies have been revealed in the literature in this field, which are mostly dedicated to developing relevant measures that can be utilized for the evaluation of vulnerable networks under different sources of uncertainty, such as daily traffic flow...

Nowadays, the necessity of accurate quantitative decision support methods is becoming a critical subject for managers as rivalry between organizations caused a more fragile economic environment and brand reputation is becoming more important. Furthermore, dealing with incidents after they happened is not accepted by customers anymore. Managers require powerful decision making tools to support t...

Recently, MOEA/D (multi-objective evolutionary algorithm based on decomposition) has achieved great success in the field of evolutionary multi-objective optimization and has attracted a lot of attention. It decomposes a multi-objective optimization problem (MOP) into a set of scalar subproblems using uniformly distributed aggregation weight vectors and provides an excellent general algorithmic ...