As multiobjective optimization problems have many solutions, evolutionary algorithms have been widely used for complex multiobjective problems instead of simulated annealing. However, simulated annealing also has favorable characteristics in the multimodal search. We developed several simulated annealing schemes for the multiobjective optimization based on this fact. Simulated annealing and evo...

In this paper, four simulated annealing based multiobjective algorithms—SMOSA, UMOSA, PSA and WMOSA have been used to solve multiobjective optimization of constrained problems with varying degree of complexity along with a new PDMOSA algorithm. PDMOSA algorithm uses a strategy of Pareto dominant based fitness in the acceptance criteria of simulated annealing and is improved. In all algorithms, ...

Although population-based algorithms are robust in solving Multi-objective Optimization Problems (MOP), they often require a large number of function evaluations. In contrast, individual-solution based algorithms are fast but can be stuck in local minima. To solve these problems, we introduce a fast and adaptive local search algorithm for MOP. Our algorithm is an individual-solution algorithm w...

This paper presents a comprehensive review of simulated annealing (SA)-based optimization algorithms. SA-based algorithms solve single and multiobjective optimization problems, where a desired global minimum/maximum is hidden among many local minima/maxima. Three single objective optimization algorithms (SA, SA with tabu search and CSA) and five multiobjective optimization algorithms (SMOSA, UM...

Thousands of equipments of the wireless local access network and the mobile devices are widely used and the demand of dynamic spectrum resources is significantly growing. How to maximize the social utility in modern technique becomes an important issue. In this paper, the simulated annealing based approach which dynamically allocates the power spectrum is proposed to enhance the system efficien...

An essential aspect of efficiency control of a three-phase induction motor is the ability to generate the optimal magnetic flux required for different operating modes. In this paper, we use the genetic algorithm (GA), the particle swarm optimization algorithm (PSO) and the simulated annealing (SA) to cope with the complexity of the problem and compute feasible and quasi-optimal magnetic flux ne...

Mobility and handoff management is a key problem of the Future Internet. Current solutions provide mobility services, such as seamless mobility, adaptive mobility, alwaysbest-connected (ABC) mobility, etc. The problem is these services work separately and ignore conflicts between them. This may lead to improve one service and degrade others. Hence, we propose multipurpose mobility as a new holi...

Supply chain network (SCN) design is to provide an optimal platform for efficient and effective supply chain management. It is an important and strategic operations management problem in supply chain management, and usually involves multiple and conflicting objectives such as cost, service level, resource utilization, etc. This paper proposes a new solution procedure based on genetic algorithms...

For the optimal size and placement of the dynamic voltage restorer (DVR) in a distribution network, in this paper the Simulated Annealing (SA) method is proposed. The multi-objective problem is converted to a single function using the goal attainment method. The obtained results show the voltage sag improvement on sensitive load nodes and other nodes in distribution system with minimum cost.

A multi-objective simulated annealing (MOSA) algorithm is described in this chapter to solve a real maintenance workforce scheduling problem (MWSP) aimed at simultaneously minimizing the workforce cost and maximizing the equipment availability. Heavy industry maintenance facilities at aircraft service centres, railroad yards and steel companies must contend with scheduling Preventive Maintenanc...