Hybrid metaheuristic solutions to inventory location routing problem

Dynamic supply chain network design with capacity planning and multi-period pricing

“…SA, presented by Kirkpatrick (1984), is a local-search based meta-heuristic approach and is still being used broadly as a powerful optimization tool (Fazel Zarandi et al, 2013). The application of SA in recently published papers (see Fattahi et al, 2014;Zhang et al, 2014;Felipe et al, 2014) shows its abilities in solving various optimization problems.…”

A metaheuristic approach to the reliable location routing problem under disruptions

“…Unlike the GTS proposed in these two studies, we consider a different neighborhood structure that can operate on both inter-and intra-routes and can search over a much wider space than the one covering only a small number of arc exchanges and customer movements. We implement the same GTS heuristic in Zhang et al (2014), to which readers can refer for details.…”

“…In the GTS heuristic, the parameters to be assigned are the same as those in Zhang et al (2014). Parameters in the SA framework are cooling speed a, initial temperature t m , freezing temperature t 0 , consecutive non-improve iterations C m , accumulated non-improve iterations maxIter and the iterations l m at each temperature.…”

Optimization of a Two-Echelon Location Lot-Sizing Routing Problem with Deterministic Demand

“…Nekooghadirli et al [40] studied a biobjective locationrouting-inventory model with multiperiod, multiproduct, stochastic demand and probabilistic travelling time among customers; their model aims to minimize the total cost and maximize the average time for delivering commodities to customers; and Zhang et al [41] presented a hybrid metaheuristic combined with simulated annealing method to solve a LIRP in a two-echelon network composed of multiple capacitated depots and final customers.…”