1,720,996 research outputs found
Direct k-routing versus cross-docking: worst-case results
No full textWe consider a firm that devises outbound routes from its plant to satisfy daily demand of the set of its n customers at minimum cost. While routes can vary daily based on demand, we assume that the firm must commit long-term to a routing strategy. We consider the following routing strategies: (i) the direct delivery of products to customers from the plant on a k-route, where a k-route is a vehicle route with at most k customers on the route, and (ii) the use of a cross-dock as an intermediate transit point by first consolidating customer demand on vehicles traveling on mainline routes, which travel from the plant to the cross-dock, and then shipping demand from the cross-dock to customers on a set of n-routes. We examine the worst-case behavior for these routing strategies and their managerial implications
A rolling horizon approach for a multi-stage stochastic fixed-charge transportation problem with transshipment
No full textWe study a fixed-charge transportation problem under stochastic and dynamic demand. We propose a multi-stage mixed integer stochastic programming formulation, where the first-stage decision is the delivery from the supplier to the retailers, while transshipment is used, in addition to classical backordering as recourse decision. The objective is the minimization of the total expected cost. We prove that this problem is NP-hard and, through a worst-case analysis, that transshipment can provide significant cost savings. Extensive computational studies are carried out to evaluate the performance of a rolling horizon approach with respect to the optimal cost. Numerical results show that this heuristic provides effective solutions in short computational time. Managerial insights are finally drawn
The value of integration of full container load, less than container load and air freight shipments in vendor–managed inventory systems
No full textWe address a long–haul transportation problem of delivering a set of products from a producer to a customer, where Full Container Load (FCL) shipments on one side and Less than Container Load (LCL) or Air Freight shipments on the other side are integrated. A Vendor-Managed Inventory (VMI) approach is used: a decision-maker has to find a periodic shipping policy that minimizes the sum of transportation cost and inventory cost, both at the producer and at the customer. This problem is defined at the tactical level implying that the initial inventory levels at the producer and at the customer are not data, but decision variables. For this problem we formulate a Mixed Integer Linear Programming model and prove its computational complexity. Furthermore, we introduce the concept of Value of Integration of FCL and LCL/Air Freight shipments and prove performance bounds to show that the integration of FCL and LCL/Air Freight shipments can lead to significant cost savings, both in the worst case and on average. Systematic computational experiments are finally carried out
Matheuristic Algorithms for the Inventory Routing Problem With Unsplit and Split Deliveries
No full textWe introduce new matheuristic algorithms for the Inventory Routing Problem with unsplit and split deliveries for both Order-Up-to Level and Maximum Level replenishment policies. The first matheuristic is based on the Capacitated Concentrator Location problem. The second is a route-based approach using routes found in other schemes as input, including the ones found in the first matheuristic. We carry out extensive experiments on benchmark instances to understand their effectiveness. The results show that they are effective and require a relatively short computational time
An improved model for estimating optimal VRP solution values
No full textSince it is computationally expensive to solve the vehicle routing problem (VRP) optimally, as this problem is NP-hard, in this technical note we study how to accurately approximate the optimal VRP tour length. In our previous papers, we developed a linear regression model including the mean and standard deviation of the modified Clarke and Wright heuristic solution values, which was able to predict the optimal VRP tour length fairly well. In this note, we find that by doing a small amount of extra work to include the minimum of the modified Clarke and Wright heuristic solution values, we can improve the predictive results substantially
Estimating optimal split delivery vehicle routing problem solution values
No full textThis paper explores the application of linear regression models to estimate the optimal solution value (i.e., the sum of tour lengths) for the Split Delivery Vehicle Routing Problem (SDVRP). We present novel models that integrate topological features along with the mean and standard deviation of feasible solution values, achieving an impressive accuracy with an error margin of approximately 3%. To obtain random feasible solutions for the SDVRP quickly, we propose a modified Clarke & Wright algorithm with split delivery (MCWSD). Our results demonstrate the potential of extending our earlier work to more complex routing problems, highlighting the importance of incorporating diverse features to obtain accurate approximations
Recent challenges in Routing and Inventory Routing: E‐commerce and last‐mile delivery
No full textIn the e-commerce era, vendors have to satisfy a large number of on-line orders, mainly from private customers, with low weight and volume, reduced delivery time, and overlap of customers' time windows. Production is made available all day long. New strategies and new technologies are emerging for deliveries. The processing time of the orders is reduced. These new features generate interesting challenges in formulating and solving Routing and Inventory Routing problems. After discussing these features and the corresponding challenges, we recall the relevant literature in Routing and Inventory Routing and provide future research directions, mainly related to routing problems with release dates, routing problems with crowdshipping, and inventory routing problems in the e-commerce era
Matheuristics with performance guarantee for the unsplit and split delivery capacitated vehicle routing problem
No full textFor the classical unsplit and split delivery capacitated vehicle routing problems, we carry out a worst-case analysis for classes of matheuristics and compare their performance on average, on a large set of benchmark instances. The matheuristics are based on the optimal solution of the bin packing problem, the capacitated concentrator location problem, and the unsplit capacitated vehicle routing problem (CVRP). These matheuristics are compared with the classical algorithms having known finite worst-case performance bound. For the unsplit CVRP, we provide a matheuristic having worst-case performance bound equal to the one of the classical algorithms, but with an average percent cost increase with respect to the optimal cost equal to 1.13%. For the split delivery case, we provide a matheuristic having worst-case performance bound 2 and an average percent cost increase with respect to the best-known cost equal to 0.64%. Moreover, this matheuristic is able to find 22 best-known solutions, 20 of which are new
A two-stage stochastic programming model for bike-sharing systems with rebalancing
No full textWe study the problem of determining the target inventory level of stations in a bike-sharing system, when bikes can be rebalanced later during the day. We propose a two-stage stochastic programming formulation, where the target inventory decisions are made at the first stage, while the recourse decisions, related to rebalancing, are made at the second stage. In the literature, the problem of determining the target inventory levels is solved without taking into account the rebalancing problem, or these two problems are solved sequentially. We prove that more efficient bike-sharing systems can be obtained by integrating these two problems. Moreover, we show that our methodology provides better results than the deterministic formulation, and consider an effective matheuristic, based on the solution of the deterministic problem, to solve the stochastic program. Finally, we compare the solutions obtained by our approach with the actual allocation of bikes in the real bike-sharing system of the city of San Francisco. The results show the effectiveness of our approach also in a realistic setting
The distribution planning process in a supply chain with multiple transportation strategies
No full textThis paper compares different approaches to solve the distribution planning process problem with
distribution strategy choice in supply chains, encompassing several production plants and several regional
warehouses that fulfill a set of retail customers with several references. The problem has been tackled considering
two different perspectives: the former is more empirical, providing a heuristic solution (Empirical model) of the
problem, while the latter is based on a mixed integer linear programming model (Analytical model). The paper
discusses the computational results obtained by applying the aforementioned approaches in terms of costs,
optimality gap and computational time to the food supply chain of an Italian subsidiary of a German group
encompassing 2 production plants located in Germany, 2 regional warehouses situated in Italy, that fulfill 200 retail
customers with 19 references. In addition to the computational results that provide a comparison among the solution
applied by the company (Rule of thumb), the Empirical model and the Analytical model, managerial insights are
underlined, in terms of applicability of the best approach within the specific company contex
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