Heuristic optimization provides a robust and efficient approach 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. The convergence rate and suitable diversity of solutions are of great importance for multi-objective evolutionary algorithms. The focu...

Dynamic optimization using evolutionary algorithms is receiving increasing interests. However, typical test functions for comparing the performance of various dynamic optimization algorithms still lack. This paper suggests a method for constructing dynamic optimization test problems using multi-objective optimization (MOO) concepts. By aggregating different objectives of an MOO problem and chan...

We propose a polynomial-time-delay polynomial-space algorithm to enumerate all efficient extreme solutions of a multi-criteria minimum-cost spanning tree problem, while only the bicriteria case was studied in the literature. The algorithm is based on the reverse search framework due to Avis & Fukuda. We also show that the same technique can be applied to the multi-criteria version of the minimu...

A suitable use of software packages for optimization problems can give the possibility to formulate design problems of robotic mechanical systems by taking into account several aspects and behaviours for optimum solutions both in design and operation. However, an important issue that can be critical to obtain practical solutions can be recognized in a proper identification and formulation of cr...

Water resources are one of the limiting factors of regional development around the Eastern and Southern Mediterranean. Scarcity and conflict, but also considerable uncertainty, inter-annual variability, and simple lack of reliable data characterize the problems of water resource management in many countries and river basins. Within the EU sponsored international RTD project OPTIMA a water resou...

In this paper, Multi-View Expectation and Maximization algorithm for finite mixture models is proposed by us to handle realworld learning problems which have natural feature splits. Multi-View EM does feature split as Co-training and Co-EM, but it considers multiview learning problems in the EM framework. The proposed algorithm has these impressing advantages comparing with other algorithms in ...

Uncertain parameters appear in many optimization problems raised by real-world applications. To handle such problems, several approaches to model uncertainty are available, such as stochastic programming and robust optimization. This study is focused on robust optimization, in particular, the criteria to select and determine a robust solution. We provide an overview on robust optimization crite...

Scheduling for the flexible job shop is very important in both fields of production management and combinatorial optimization. However, it quit difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. The combining of several optimization criteria induces additional complexity and new problems. In this paper, a...

in this paper, firstly by using a mixed linear programming a new model of locating facilities with limited capacity is presented to design a closed-loop supply chain in a multi-product and multi-period mode. then, using a robust optimization approach, the proposed model decreases in non-deterministic expansion. the results show that the proposed model can handle facility capacity in a closed lo...

Inventory management requires thousands or millions of individual transactions each year. Classification the items influences results inventory management. Traditionally, this is usually classified with considering an annual dollar usage criterion but maybe other criteria such as lead time, criticality, perishability, cost, and demand type can be affected on that classification. have more than ...