Analysis and Evaluation of Incentive Compatible Dynamic Mechanisms for Carrier Collaboration

This paper introduces a framework for carrier dynamic collaboration. In particular it proposes and analyzes dynamic collaborative mechanisms that are incentive compatible. The dynamic collaborative environment is characterized by a set of carriers that have a proprietary set of customers that generate a stream of random demands over time. The proposed collaborative mechanism is such that upon each demand arrival, each carrier has the incentive to submit the arrived shipment or service request to the collaborative mechanism. Intuition about the efficiency and workings of the collaborative mechanism is developed. A general framework to formulate and study collaborative frameworks among transportation carriers is proposed. A truckload pickup-and-delivery collaborative environment is simulated and results are analyzed

Interaction between intelligent agent strategies for real-time transportation planning

In this paper we study the real-time scheduling of time-sensitive full truckload pickup-and-delivery jobs. The problem involves the allocation of jobs to a fixed set of vehicles which might belong to different collaborating transportation agencies. A recently proposed solution methodology for this problem is the use of a multi-agent system where shipper agents offer jobs through sequential auctions and vehicle agents bid on these jobs. In this paper we consider such a system where both the vehicle agents and the shipper agents are using profit maximizing look-ahead strategies. Our main contribution is that we study the interrelation of these strategies and their impact on the system-wide logistical costs. From our simulation results, we conclude that the system-wide logistical costs (i) are always reduced by using the look-ahead strategies instead of a myopic strategy (10–20%) and (ii) the joint effect of two look-ahead strategies is larger than the effect of an individual strategy. To provide an indication of the savings that might be realized under centralized decision making, we benchmark our results against an integer programming approach

Inter-firm collaboration in transportation

Dans la littérature académique et professionnelle relative au transport de marchandise, il y a longtemps que les méthodes de planification avancées ont été identifiées comme un moyen de dégager des économies grâce à une efficacité accrue des opérations de transport. Plus récemment, la collaboration interentreprises dans la planification du transport a été étudiée comme une source de gain supplémentaire en efficacité et, par conséquent, une opportunité pour dégager de nouvelles économies pour les collaborateurs. Cependant, la mise en œuvre d'une collaboration interentreprises en transports soulève un certain nombre d’enjeux. Cette thèse aborde trois thèmes centraux de la collaboration interentreprises et démontre les contributions via des études de cas dans l’industrie forestière et du meuble. Premièrement, les moyens technologiques pour soutenir une collaboration en planification du transport sont étudiés. Un système d’aide à la décision supportant la collaboration en transport forestier est présenté. Deuxièmement, le partage entre les collaborateurs du coût commun en transport est étudié. Une méthode de répartition du coût de transport tenant compte de l'impact - l’augmentation du coût de transport - des exigences inégales entre des collaborateurs est proposée. Troisièmement, la création de groupes collaboratifs - des coalitions - dans un ensemble de collaborateurs potentiel est étudiée. Un modèle réseau pour la formation d’une coalition selon les intérêts d’un sous-ensemble de collaborateurs adoptant ou pas un comportement opportuniste est détaillé. De plus, pour soutenir l'étude des thèmes précédents, la thèse comprend deux revues de la littérature. Premièrement, une revue sur les méthodes de planification et les systèmes d’aide à la décision en transport forestier est présenté. Deuxièmement, à travers la proposition d'un cadre pour créer et gérer une collaboration en transport et, plus généralement en logistique, une revue de travaux sur le transport et la logistique collaborative est offerte.In the academic and professional literature on freight transportation, computer-based planning methods have a long time ago been identified as a means to achieve cost reduction through enhanced transportation operations efficiency. More recently, inter-firm collaboration in transportation planning has been investigated as a means to provide further gains in efficiency and, in turn, to achieve additional cost reduction for the collaborators. However, implementation of inter-firm collaboration in transportation raises a number of issues. This thesis addresses three central themes in inter-firm collaboration and exemplifies the contributions in case studies involving collaboration in furniture and forest transportation. First, technological means to enable collaboration in transportation planning are studied. Embedding a computer-based planning method for truck routing, a decision support system enabling collaborative transportation is presented. Second, sharing the common transportation cost among collaborators is studied. A cost allocation method taking into account the impact – an increase of the transportation cost – of uneven requirements among collaborators is proposed. Third, building collaborating groups (i.e. coalitions) among a set of potential collaborators is studied. A network model for coalition formation by a subset of self-interested collaborators adopting or not an opportunistic behaviour is detailed. Moreover, to support the study of the aforementioned themes, the thesis includes two literature reviews. First, a survey on planning methods and decision support systems for vehicle routing problem in forest transportation is presented. Second, through the proposition of a framework for building and managing collaboration in transportation and, more generally in logistics, a survey of works on collaborative transportation and logistics is given

The Benefits of Information Sharing in Carrier-Client Collaboration

This dissertation includes three related papers to investigate different methods that can help transport providers improve their operational efficiency. The first paper models and measures the profit improvement trucking companies can achieve by collaborating with their clients to obtain advance load information (ALI). The core research method is to formulate a comprehensive and flexible mixed integer mathematical model and implement it in a dynamic rolling horizon context. The findings illustrate that access to the second day ALI can improve the profit by an average of 22%. We also found that the impact of ALI depends on radius of service and trip length but statistically independent of load density and fleet size. The second paper investigates the following question of relevance to truckload dispatchers striving for profitable decisions in the context of dynamic pick-up and delivery problems: since not all future pick-up/delivery requests are known with certainty, how effective are alternative methods for guiding those decisions? We propose an intuitive policy and integrate it into a new two-index mixed integer programming formulation, which we implement using the rolling horizon approach. On average, in one of the practical transportation network settings, the proposed policy can, with just second-day ALI, yield an optimality ratio equal to almost 90% of profits in the static optimal solution. We enhance the proposed policy by adopting the idea of a multiple scenario approach. In comparison to other dispatching methods, our proposed policies were found to be very competitive in terms of solution quality and computational efficiency. Finally, inspired by a real-life third party logistic provider, the third paper addresses a dynamic pickup and delivery problem with full truckload (DPDFL) for local operators. The main purpose of this work is to investigate the impact of potential factors on the carriers’ operational efficiency. These factors, which are usually under managerial influence, are vehicle diversion capability, the DPDFL decision interval, and how far in advance the carrier knows of clients’ shipment requirements; i.e., ALI. Through comprehensive numerical experiments and statistical analysis, we found that the ALI and re-optimization interval significantly influence the total cost, but that diversion capability does not. A major contribution of this work is that we develop an efficient benchmark solution for the DPDFL’s static version by discretization of time windows. We observed that three-day ALI and an appropriate decision interval can reduce deviation from the benchmark solution to less than 8%