Smart logistics

This lecture focuses on Smart Logistics referring to these intelligent managerial decisions related to the design, operations and control of the transportation chain processes in an efficient and cost-effective way. The starting point for Smart Logistics is the key observation that the real-life world is stochastic and changing over time. Any logistics decision ignoring these aspects is bound to be sub-optimal once realized. Due to these real-life complexities, coping with time-dependent and stochastic environments is a difficult problem in Freight Transport & Logistics. Rather than focusing on idealized logistics problems in the transportation chain, I will focus on different real-life variants of these challenging problems. In this lecture, I will outline and discuss three main research themes on which I will focus in my chair on Freight Transport & Logistics

A stochastic variable size bin packing problem with time constraints

In this paper, we extend the classical Variable Size Bin Packing Problem (VS-BPP) by adding time features to both bins and items. Speciffically, the bins act as machines that process the assigned batch of items with a fixed processing time. Hence, the items are available for processing at given times and are penalized for tardiness. Within this extension we also consider a stochastic variant, where the arrival times of the items have a discrete probability distribution. To solve these models, we build a Markov Chain Monte Carlo (MCMC) heuristic. We provide numerical tests to show the different decision making processes when time constraints and stochasticity are added to VSBPP instances. The results show that these new models entail safer and higher cost solutions. We also compare the performance of the MCMC heuristic and an industrial solver to show the effciency and the effcacy of our method

Vehicle routing with stochastic time-dependent travel times

Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the traffic congestion is captured in an analytical way using queueing theory. The congestion is then applied to the VRP problem. In this paper, we introduce the variability in traffic flows into the model. This allows for an evaluation of the routes based on the uncertainty involved. Different experiments show that the risk taking behavior of the planner can be taken into account during optimization. As more weight is given to the variability component, the resulting optimal route will take a slightly longer travel time, but will be more reliable. We propose a powerful objective function that is easily implemented and that captures the trade-off between the average travel time and its variance. The evaluation of the solution is done in terms of the 95th-percentile of the travel time distribution (assumed to be lognormal), which reflects well the quality of the solution in this stochastic time-dependent environment

Competitive solutions for cooperating logistics providers

This paper discusses solutions for gain sharing in consortia of logistic providers where joint planning of truckload deliveries enables the reduction of empty kilometres. The highly competitive nature of freight transport markets necessitates solutions that distinguish among the logistics providers based on their characteristics, even in situations with two players only. We introduce desirable properties in these situations and propose a solution that satisfies such properties. By comparing the existing solutions against the introduced properties we demonstrate the advantages of our proposed solution

Collaborative replenishment in the presence of intermediaries

In complex supply chains, downstream buyers would often replenish individually from intermediaries instead of directly dealing with original manufacturers. Although collaborative replenishment from intermediaries might generate benefits, significant cost reductions could be achieved when direct replenishments from manufacturers are considered. This paper constructs a general model to study collaborative replenishment in multi-product chains with alternative sources of supply—i.e., manufacturers and intermediaries. A collaborative organization determines the optimal choices of replenishment sources on behalf of its members to minimize collective costs. We introduce a class of cooperative games associated with these situations and give sufficient conditions for their concavity. We investigate the choice of allocation rule and its effect on supply chain efficiency when buyers strategically participate in the collaborative organization. We prove that the Shapley value coordinates the supply chain, i.e., it makes complete participation the best strategy for buyers even under asymmetric information. This setting is compared with an alternative structure where buyers can only collaborate in source-specific replenishment organizations that purchase all requested products either from intermediaries or manufacturers. Although there are always participation strategies that result in minimum collective cost, it is impossible to find allocation rules for source-specific replenishment organizations that always motivate the buyers to choose such strategies.</p

Integrating passenger and freight transportation : model formulation and insights

Integrating passenger and freight flows creates attractive business opportunities because the same transportation needs can be met with fewer vehicles and emissions. This paper seeks an integrated solution for the transportation of passenger and freight simultaneously, so that fewer vehicles are required. The newly introduced problem concerns scheduling a set of vehicles to serve the requests such that a part of the journey can be carried out on a scheduled passenger transportation service. We propose an arc-based mixed integer programming formulation for the integrated transportation system. Computational results on a set of instances provide a clear understanding on the benefits of integrating passenger and freight transportation in the current networks, considering multi-modality of traditional passenger-oriented transportation modes, such as taxi, bus, train or tram

Coordination and analysis of barge container hinterland networks

We analyze the import hinterland supply chain from the perspective of both the inland terminal operator and of the shippers. In the hinterland supply chain, the interests of capital-intensive terminal operators are not aligned with the interests of shippers. Therefore, we define the joint shipment quantity for container freight distribution that counts for the specific nature of barge transportation. We consider the direct and the tour coordination policies. Based on empirical data, the cost-effectiveness and the performance of these policies is evaluated in detail. Analytical results give insights into the trade-off between the variable transportation costs and the inventory holding costs

On characterization of the core of lane covering games via dual solutions

The lane covering game (LCG) is a cooperative game where players cooperate to reduce the cost of cycles that cover their required lanes on a network. We discuss the possibilities/impossibilities of a complete characterization of the core via dual solutions in LCGs played among a collection of shippers, each with a number of service require-ments along some lanes, and show that such a complete characterization is possible if each shipper has at most one service requirement