The aim of a multi-mode resource-constrained project scheduling problem (MRCPSP) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). These goals vary with managers or decision makers of any organization who should determine suitable objective(s) considering organization strategi...

In this paper, we propose sequential Monte Carlo simulated annealing (SMC-SA), a populationbased simulated annealing algorithm, for continuous global optimization. SMC-SA incorporates the sequential Monte Carlo method to track the converging sequence of Boltzmann distributions in simulated annealing, such that the empirical distribution will converge weakly to the uniform distribution on the se...

Increasing economy’s resistance against the menace of sanctions, various risks, shocks, and internal and external threats are one of the main national policies which can be implemented through bank investments. Investment project selection is a complex and multi-criteria decision-making process that is influenced by multiple and often some conflicting objectives. This paper studies portfolio inve...

in this paper, a multi-product continues review inventory control problem within batch arrival queuing approach (mqr/m/1) is modeled to find the optimal quantities of maximum inventory. the objective function is to minimize summation of ordering, holding and shortage costs under warehouse space, service level, and expected lost-sales shortage cost constraints from retailer and warehouse viewpoi...

We present a parallel computational environment used to determine conductivity properties of human head tissues when the effects of skull inhomogeneities are modeled. The environment employs a parallel simulated annealing algorithm to overcome poor convergence rates of the simplex method for larger numbers of head tissues required for accurate modeling of electromagnetic dynamics of brain funct...

This paper presents a method based on simulated annealing to learn reactive behaviors. This work is related with multi-agent systems. It is a first step towards automatic generation of sensorimotor control architectures for completing complex cooperative tasks with simple reactive mobile robots. The controller of the agents is a neural network and we use a simulated annealing techniques to lear...