Artículos de revistas
Managing Distribution in Supply Chain Networks
Dondo, Rodolfo Gabriel; Mendez, Carlos Alberto; Cerda, Jaime; Managing Distribution in Supply Chain Networks; American Chemical Society; Industrial & Engineering Chemical Research; 48; 22; 12-2009; 9961-9978
Dondo, Rodolfo Gabriel
Mendez, Carlos Alberto
This paper presents a novel optimization approach to the short-term operational planning of multiechelon multiproduct transportation networks. Distribution activities commonly arising in real-world chemical supply chains involve the shipping of a number of commodities from factories to customers directly and/or via distribution centers and regional warehouses. To optimally manage such complex distribution systems, a more general vehicle routing problem in supply chain management (VRP-SCM) has been defined. The new VRP-SCM problem better resembles the logistics activities to be planned at multisite manufacturing firms by allowing multiple events at every location. In this way, two or more vehicles can visit a given location to perform pickup and/or delivery operations, and vehicle routes may include several stops at the same site, i.e., multiple tours per route. More important, the allocation of customers to suppliers and the quantities of products shipped from each source to a particular client are additional model decisions. Both the capacitated vehicle routing problem (VRP) and the pickup-and-delivery problem (PDP) can be regarded as particular instances of the new VRP-SCM. The proposed MILP mathematical formulation for the VRP-SCM problem relies on a continuous-time representation and applies the general precedence notion to model the sequencing constraints establishing the ordering of vehicle stops on every route. The approach provides a very detailed set of optimal vehicle routes and schedules to meet all product demands at minimum total transportation cost. Several examples involving up to 26 locations, four products, and six vehicles housed in four different depots have been solved to optimality in very short CPU times.