A parameter-tuned genetic algorithm for multi-product economic production quantity model with space constraint, discrete delivery orders and shortages

Optimization of mixed integer nonlinear economic lot scheduling problem with multiple setups and shelf life using metaheuristic algorithms

“…In order to deal with infeasibility, the penalty policy is applied, which is the transformation of a constrained optimization problem into an unconstrained one. It can be attained by adding or multiplying a specific amount to/by the objective function value according to the amount of obtained constraints' violations in a solution [25].…”

A hybrid genetic and imperialist competitive algorithm for green vendor managed inventory of multi-item multi-constraint EOQ model under shortage

“…Here, it is assumed that the vendor pays the ordering and holding costs on behalf of the buyer as a part of the mentioned agreement; the buyer paying no cost. This assumption has also been taken into considerations in prior studies such as [22,26,27,35] where supply chain integration in VMI has been discussed.…”

“…Many researchers have successfully used meta-heuristic methods to solve complicated optimization problems in different fields of scientific and engineering disciplines. Some of these meta-heuristic algorithms are: simulating annealing [39,40], threshold accepting [41], Tabu search [42], genetic algorithm [35,43,44], particle swarm optimization [45][46][47][48][49][50], neural networks [51], ant colony optimization [28,52], evolutionary algorithm [53,54], harmony search [55,56] and gravitational search algorithm [57]. Among these algorithms, the population-based ones are usually preferred to others and in some cases show better performances.…”

Genetic application in a facility location problem with random demand within queuing framework

“…The involved processes in central design have wide variety from manufacturing processes, to quality control or even parameter tuning in meta-heuristic algorithms (see for example Tsapatsaris and Kotzekidou 2004;Najafi et al 2009;Pasnadideh et al 2010). The CCD is the most popular and efficient class of designs used for fitting a second order model.…”