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, ...

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...

This paper addresses a multi-objective mathematical model for the mixed-model two-sided assembly line balancing and worker assignment with different skills. In this problem, the operation time of each task is dependent on the skill of the worker. The following objective functions are considered in the mathematical model: (1) minimizing the number of mated-stations (2), minimizing the number of ...

The purpose of this paper is to present a linear quadratic simultaneous multi-model stabilizing approach based on simulated annealing algorithm. This method is developed to design robust control laws for AC drives. A specific application to a synchronous self-controlled motor is detailed. The main objective here is design a robust controller with predetermined structure. Experimental results ar...

In this paper, we propose a population-based optimization algorithm, Sequential Monte Carlo Simulated Annealing (SMC-SA), for continuous global optimization. SMC-SA incorporates the sequential Monte Carlo method to track the converging sequence of Boltzmann distributions in simulated annealing. We prove an upper bound on the difference between the empirical distribution yielded by SMC-SA and th...

This paper investigates the problem of selecting and scheduling a set of projects among available projects. Each project consists of several tasks and to perform each one some resource is required. The objective is to maximize total benefit. The paper constructs a mathematical formulation in form of mixed integer linear programming model. Three effective metaheuristics in form of the imperialis...

Considering the characteristics of Simulated Annealing Algorithm (SAA), based on the agents’ perception and retroaction to their surroundings, in this paper a new algorithm called Multi-agent Annealing Algorithm (MAA) is presented. And the global convergence of MAA is gotten. Finally, we make several numerical experiments to compare MAA with SAA and Genetic Algorithm (GA) by three classical tes...