This paper presents a review of genetic algorithms in integrated process planning and scheduling problems. According to the literature information, process planning and scheduling are two functions that were sequentially carried out in a manufacturing system, where scheduling was performed after process plans had been generated. Their integration highly improves the performance and efficiency o...

Most of the metaheuristics can efficiently solve unconstrained problems; however, their performance may degenerate if the constraints are involved. This paper proposes two constraint handling approaches for an emerging metaheuristic of Cohort Intelligence (CI). More specifically CI with static penalty function approach (SCI) and CI with dynamic penalty function approach (DCI) are proposed. The ...

Cellular Automata can be successfully applied in image processing. In this paper, we propose a new edge detection algorithm, based on cellular automata to extract edges of different types of images, using a totalistic transition rule. The metaheuristic PSO is used to find out the optimal and appropriate transition rules set of cellular automata for edge detection task. This combination increase...

We suggest a new heuristic for solving unconstrained continuous optimization problems. It is based on a generalized version of the variable neighborhood search metaheuristic. Different neighborhoods and distributions, induced from different metrics are ranked and used to get random points in the shaking step. We also propose VNS for solving constrained optimization problems. The constraints are...

the present study is concerned with optimal shape determination of inhomogeneous and temperature dependent domains under steady state heat conduction. such situations are important in many thermal design problems, especially in shape design of electronic components and chips. in the present paper, we formulate the shape optimization problem based on volume minimization of heat conductive materi...

Rotary Unmanned Aerial Vehicles (RUAVs) suffer in average Northern Irish winters due to heavy wind preventing vital tasks from being performed the economy, such as search and rescue or civil engineering observations. This work provides enhanced stability of RUAVs under disturbances by using metaheuristic algorithms select optimal controller gains. Previous demonstrated how Particle Swarm Optimi...

This paper presents a metaheuristic approach based on the Honey Bee Mating Algorithm (HBMA) to the problem of hydropower reservoir optimization. As shortage in power resources becomes more and more pressing, the issue of obtaining more power using less primary energy resources, in general, and less water resources, in particular, becomes an important target for the efficient usage of hydropower...

This paper presents an asynchronous parallel metaheuristic for the period vehicle routing problem (PVRP). The PVRP generalizes the classical vehicle routing problem by extending the planning period from a single day to M days. The algorithm proposed is based on concepts used in parallel genetic algorithms and local search heuristics. The algorithm employs the Island model in which the migration...

in financial matters, portfolio can be interpreted as a combination or a series of investments hold by an institution or a person. portfolio optimization is one of the most important concerns of investors for maximizing the portfolio in financial markets. the formation of portfolio is a vital and critical decision for the companies.  in fact, the selection of portfolio is to specify the capital...

In this paper a metaheuristic algorithm composed of particle swarm, ray optimization, and harmony search (HRPSO) is presented for optimal design of truss structures. This algorithm is based on the particle swarm ray origin making is used to update the positions of the particles, and for enhancing the exploitation of the algorithm the harmony search is utilized. Numerical results demonstrate the...