A reactive GRASP and path relinking for a combined production–distribution problem

A fuzzy solution approach for a multi-objective integrated production-distribution model with multi products and multi periods under uncertainty

“…In some sectors, they even dominate production costs. Ideally, this is why any cost reduction effort should encompass production planning and distribution planning (Boudia et al, 2007). It is a challenging problem for manufacturers to optimize their supply chain (Bard & Nananukul, 2010).…”

“…Note that the considered problem belongs to a class of NP-hard ones and it is reduced to the VRP, which is a well-known NP-hard problem, in a single period case (Boudia et al, 2007). Lei et al (2006) formulated the production, inventory and distribution routing problem as a mixed-integer model.…”

“…The main advantage lies in its ability to simultaneously coordinate the production, inventory and transportation operations of the entire planning horizon, without any need to aggregate the demand or relax constraints on transportation capacities. Boudia et al (2007) developed a similar production, distribution problem for one product over a multi-period horizon and used the GRASP method with path relinking. Boudia and Prins (2009) used a memetic algorithm with population management to solve the model and compared the results with a two-phase heuristic and GRASP.…”

Multi-period stochastic optimization problems in transportation management

“…As pointed out in the literature surveys by [Chen, 2004], [Chen, 2010], and [Vidal & Goetschalckx, 1997], most models focus on coordination either at the strategic level or at the tactical level: the objective is then to design efficient supply networks or to take transportation costs into account in the framework of production planning. Some authors, like [Boudia et al, 2007], [Wang & Cheng, 2009], or [Zegordi et al, 2010], deal with operational decisions, but this stream of literature is quite recent and typically places the emphasis on production scheduling issues (see [Chen, 2010]). …”

“…The associated planning processes, such as production scheduling and transportation planning, have been thoroughly investigated in the operations management literature, and numerous optimization models tackle production and transportation decisions. Some of these models integrate production-transportation decisions, with a view towards better coordination of the supply chain; representative examples of this trend of research can be found, for instance, in [Boudia et al, 2007], [Chen, 2004], [Chen, 2010], [Fumero & Vercellis, 1999], [Melo & Wolsey, 2010], [Sarmiento & Nagi, 1999], [Erengüç et al, 1999], [Stecke & Zhao, 2007], [Tang et al, 2007], [Vidal & Goetschalckx, 1997], [Wang & Cheng, 2009], [Yung et al, 2006], and [Zegordi et al, 2010]. As pointed out in the literature surveys by [Chen, 2004], [Chen, 2010], and [Vidal & Goetschalckx, 1997], most models focus on coordination either at the strategic level or at the tactical level: the objective is then to design efficient supply networks or to take transportation costs into account in the framework of production planning.…”