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There are several engineering problems that can be modeled as an optimization task with multiple possible solutions. Locating all the global or local optima in a single run is the main challenge of such optimization problems that are called Multi-Modal Optimization Problems (MMOP). Classical methods usually utilize several restart points and multiple runs in the hope that a different solution may be discovered every run. Evolutionary algorithms (EAs) due to their population based approach have some advantages over classical optimization techniques. They maintain a population of possible solutions, which are processed every generation, and if the multiple solutions can be preserved over all these generations, then at termination of the algorithm we will have multiple optimal solutions, rather than only the best solution. Therefore, preserving the population diversity as well as employing a good memorization mechanism (for saving the optimal solutions) must be utilized in EA based multi-modal algorithms. In this special session, researchers are invited to submit their original works based on evolutionary and swarm intelligent algorithms for solving MMOP.

دکتر مهدي افتخاري

Multi-Modal optimization based on swarm and evolutionary algorithms

Software engineering has many problems which can be modeled as search problems. Currently most of these problems are solved by human. It is required to move software engineering problems from human-based search to machine-based search. Search-Based Software Engineering (SBSE) is a new track in software engineering which is aimed to use optimization techniques (swarm intelligence, evolutionary algorithms, etc) to find optimal or near-optimal solutions for software engineering problems. The SBSE focuses on different areas of software engineering such as software testing, architecture, design, requirements. We invite the submission of high quality papers describing novel and original work in all areas of SBSE in this special session.

دکتر رضا اکبري

Search-Based Software Engineering (SBSE)

Constraint optimization(so calledconstrained optimization) is the process ofoptimizing an objective function with respect to some constraints. Solutions that do not satisfy all of the constraints are infeasible. So, complex engineering problems with large number of constraints are hard to solve. In this special session, researchers are invited to submit their original works for solving constraint engineering optimization problems with heuristic optimization algorithms. Especially, solving some standard engineering problems including: the welded beam design problem, the pressure vessel design problem, the tension/compression spring design problem, and the speed reducer design problem are suggested.

دکتر عصمت راشدي

Solving constraint engineering optimizationproblems using heuristic optimization algorithms