Models for Reducing Deadheading through Carrier and Shipper Collaboration

The competitive nature in the trucking industry has forced trucking firms to develop innovative solutions to improve their operational efficiency and decrease marginal costs. There is also a great need to reduce deadheading miles of heavy trucks to help reduce the amount of air pollutants they emit. One way carriers and shippers are attempting to accomplish these goals is through various collaborative operational strategies. This work focuses on developing multiple collaboration frameworks and formulating optimization models for each framework that demonstrates the operations and reveals the potential cost savings of each framework.;The first collaboration framework focuses on how a medium level shipper or carrier can introduce collaboration in their operations by fulfilling a collaborative carrier\u27s or shipper\u27s delivery requests on its backhaul route. Two optimization models are developed to route the carrier of interest\u27s backhaul routes and select collaborative shipments to fulfill; one is formulated as an integer program and the other is formulated as a mixed integer program. Two solution methodologies, a greedy heuristic and tabu search, are used to solve the two problems, and numerical analysis is performed with a real world freight network. Numerical analysis on a real world freight network reveals that the percentage of cost savings for backhaul routes can be as high as 27%.;The second collaboration framework focuses on a group of shippers that collaborate their operations and form cycles between their long-haul shipping lanes. If the shippers provide the bundled lanes, as loops, to a common carrier they can realize cost savings from the carrier. The problem is formulated as a mixed integer program and forms least cost loops between the shipping lanes. A tabu search heuristic is used to solve the second collaboration framework and results using a real freight network reveal collaborative network costs savings between 7% to 12%. Three cost allocation mechanisms are proposed for the problem to distribute the costs to the shippers involved in the collaboration and computational results are provided for each of the allocation mechanisms

Shipper collaboration matching: fast enumeration of triangular transports with high cooperation effects

The logistics industry in Japan is facing a severe shortage of labor. Therefore, there is an increasing need for joint transportation allowing large amounts of cargo to be transported using fewer trucks. In recent years, the use of artificial intelligence and other new technologies has gained wide attention for improving matching efficiency. However, it is difficult to develop a system that can instantly respond to requests because browsing through enormous combinations of two transport lanes is time consuming. In this study, we focus on a form of joint transportation called triangular transportation and enumerate the combinations with high cooperation effects. The proposed algorithm makes good use of hidden inequalities, such as the distance axiom, to narrow down the search range without sacrificing accuracy. Numerical experiments show that the proposed algorithm is thousands of times faster than simple brute force. With this technology as the core engine, we developed a joint transportation matching system. The system has already been in use by over 150 companies as of October 2022, and was featured in a collection of logistics digital transformation cases published by Japan's Ministry of Land, Infrastructure, Transport and Tourism.Comment: 16 pages, 7 figure

Service level, cost and environmental optimization of collaborative transportation

Less than truckload is an important type of road-based transportation. Based on real data and on a collaboration with industry, we show that a collaborative approach between companies offers important benefits. We propose to develop partnerships between shipping companies and to synchronize their shipments. Four operational collaborative schemes with different objectives are developed. The first one focuses on minimizing shipping costs for shippers. The second and third ones minimize the carrier’s costs and the environmental cost, respectively. The fourth one is a combination of all three. The results of our computational experiments demonstrate that collaboration lead to significant cost reductions

Iterative Combinatorial Auction for Carrier Collaboration in Logistic Services

In collaborative logistics, multiple carriers form a network to share their transportation capacities. Collaboration among carriers results in improved resource utilization and, therefore, reduced costs. In this thesis, we propose an auction-based model for carrier collaboration in transportation services. The model achieves carrier collaboration through facilitating the negotiation among carriers over a group of shipping orders required by one or a group of shippers. The negotiation is conducted through a combinatorial iterative auction mechanism with the objective of minimizing the carriers’ overall costs. We first present a centralized carrier collaboration problem model in which a central entity has all required information to compute an optimal solution. We then consider a more realistic game theoretic setting where auction-based mechanism is applied to deal with self-interests of carriers. Compared with one-shot auctions, the proposed iterative bidding framework has the properties of reducing carriers’ information revelation and accommodating dynamic changes during the bidding process. Experimental results show that the procurement cost performance and the quality of solutions computed using the proposed iterative auction model is close to that of the optimal solutions

Minimum cost network design in strategic alliances

Strategic alliances are established between firms to improve their competitiveness in markets and generally appear in the form of joint ventures. Such collaborative efforts require centralized planning, and the survival of the alliance largely depends on the success of joint planning processes. In this regard, we investigate the opportunities that centralized collaboration can offer to firms when designing their service networks. Apart from the classical fixed and variable costs associated with the network design, we also consider transaction costs induced by the formation of the alliance, which can broadly be defined as cost components related to the coordination and monitoring of the people, efforts and resources. We concentrate on bilateral alliances and develop alternative models for solving their associated network design problem. We also adopt a state-of-the-art heuristic to solve large-scale instances. Our findings confirm that accounting for the transaction cost in network design is vital for the alliance. These transaction costs can be high enough to even render the collaboration unattractive. Hence, careful data collection and model treatment are required before deciding whether to form an alliance.</p

Profit Allocation of E-Commerce Logistics Enterprise Alliance Based on Revised Shapely: Under the Circumstance of Warehouse Overload

This paper introduces the impact factor set, which includes input cost value, risk share coefficient, leadership in industry, market influence and the desire of participation, to revise the classic Shapley value, and use the revised Shapely value to research the profit allocation problem of an E-commerce logistics enterprise alliance under the circumstance of warehouse overload. A numerical example is presented to demonstrate the feasibility of the revised Shapely value. The result indicates that the revised Shapely value can objectively reflect the regulating effect of impact factors, show the differences between the core enterprise and general enterprises in an alliance, and promote the rationality and equity of alliance profit allocation

Collaborative Logistics in Vehicle Routing

Less-Than-Truckload (LTL) carriers generally serve geographical regions that are more localized than the inter-city routes served by truckload carriers. That localization can lead to urban freight transportation routes that overlap. If trucks are traveling with less than full loads there may exist opportunities for carriers to collaborate over such routes. That is, Carrier A will also deliver one or more shipments of Carrier B. This will improve vehicle asset utilization and reduce asset-repositioning costs, and may also lead to reduced congestion and pollution in cities. We refer to the above coordination as “collaborative routing”. In our framework for collaboration, we also propose that carriers exchange goods at logistics platforms located at the entry point to a city. This is referred to as “entry-point collaboration”. One difficulty in collaboration is the lack of facilities to allow transfer of goods between carriers. We highlight that the reduction in pollution and congestion under our proposed framework will give the city government an incentive to support these initiatives by providing facilities. Further, our analysis has shown that contrary to the poor benefits reported by previous work on vehicle routing with transshipment, strategic location of transshipment facilities in urban areas may solve this problem and lead to large cost savings from transfer of loads between carriers. We also present a novel integrated three-phase solution method. Our first phase uses either a modified tabu search, or a guided local search, to solve the vehicle routing problems with time windows that result from entry-point collaboration. The preceding methods use a constraint programming engine for feasibility checks. The second phase uses a quad-tree search to locate facilities. Quad-tree search methods are popular in computer graphics, and for grid generation in fluid simulation. These methods are known to be efficient in partitioning a two-dimensional space for storage and computation. We use this efficiency to search a two-dimensional region and locate possible transshipment facilities. In phase three, we employ an integrated greedy local search method to build collaborative routes, using three new transshipment-specific moves for neighborhood definition. We utilize an optimization module within local search to combine multiple moves at each iteration, thereby taking efficient advantage of information from neighborhood exploration. Extensive computational tests are done on random data sets which represent a city such as Toronto. Sensitivity analysis is performed on important parameters to characterize the situations when collaboration will be beneficial. Overall results show that our proposal for collaboration leads to 12% and 15% decrease in route distance and time, respectively. Average asset utilization is seen to increase by about 5% as well

Collaborative truckload transportation procurement with multiple coalitions

Gönderici işbirliği, son yıllarda ortaya çıkmış yeni bir işbirliği türüdür ve tedarik zinciri yönetiminde kurumlar arası yatay işbirliği sınıfına girmektedir. Sert rekabet koşulları, kaynak yetersizliği, iklim değişimi, güvenlik sorunları ve yeni kanuni düzenlemeler firmalar üzerindeki baskıyı artırmış ve geleneksel düşünce kalıplarını zorlayan yeni çözümler aramaya itmiştir. İşbirliği; daha geniş ve bütün sistemi kapsayan bir bakış açısı getirmesi nedeniyle yeni fırsatlar sunan bir strateji olarak görülmektedir. Gönderici işbirliğinde taşıyıcı firmalardan taşımacılık hizmeti alan bir grup gönderici firma bir araya gelir; ve taşıyıcı firmalarla grup olarak pazarlık yaparlar. Göndericiler işbirliği yapmak istediklerinde; hangi göndericilerin işbirliğine dahil edileceği, hangi göndericilerin rotalarının arka arkaya ekleneceği, ve oluşturulan rota birleştirme çözümünden doğan toplam maliyetin göndericilere ve hatta her bir rotaya dağıtılması konularında en iyi kararları vermek durumundadırlar. Literatürdeki çalışmalar işbirliği yapan göndericilerin tek bir koalisyon kurduğunu varsaymış ve bu tek koalisyonunun kurulması, devamı ve genişletilmesi konularını ele almışlardır. Verilen bir koalisyon ve bu koalisyon için hesaplanan en küçük maliyetli çözüm için adil bir maliyet paylaşımı olup olmadığını konu almışlardır. Buna ek olarak, verilen bir koalisyon, çözüm ve maliyet paylaşma mekanizması için koalisyona katılmak isteyen yeni bir göndericinin koalisyona alınıp alınmaması kararını konu alan çalışmalar da mevcuttur. Büyük ölçekli gönderici işbirliği ağlarında sadece tek bir koalisyona izin verilmesi koordinasyonu zorlaştırmakta ve kabul edilebilir maliyet dağıtımına sahip geniş çaplı bir çözüm bulunmasını zorlaştırmaktadır. Bu çalışmada birden fazla ayrışık koalisyon içerebilen tam kamyon yükü gönderici işbirliği ağları ele alınmıştır. Her biri adil maliyet dağıtımına sahip, ayrık koalisyonlardan oluşan en düşük toplam maliyetli koalisyon yapısının bulunması amaçlanmıştır. Gönderici ve rota sayıları arttıkça ve operasyonel kısıtlar eklendikçe bu kararları en iyi biçimde vermek gittikçe zorlaşmaktadır. Gerçek hayat durumlarında problem boyutlarının çok büyük olması beklendiği için özellikle büyük ölçekli problem örneklerinin çözümüne yönelik sezgisel algoritmalar geliştirilmiştir.We study formation of stable coalitions given a set of shippers and their lanes corresponding to regularly scheduled truckload shipment. In this thesis, selecting participants, deciding who should participate with whom, calculating the lowest cost operational solution and allocating the system-wide cost to the participants stand out as important problems. Collaborating shippers try to identify tours which consist of regularly scheduled shipment with minimal empty truck movements. Then, they must allocate the total cost of the collaborative solution to the participated firms and individual lanes such that the collaborative solution remains attractive to the participants. In the literature, solving the optimization problem minimization the total cost and allocating the calculated minimum cost are treated as successive but distinct phases. The cost minimizing optimization problem is solved with well-known operation research methods, while cooperative game theory concepts are used for cost allocation. The minimum cost solution may render finding an acceptable cost allocation impossible. Besides, similar works in the literature assume that the collaborating firms will forge a single grand coalition. However, as the collaboration grows in size, a single grand coalition may become impractical and also it might leave several lanes out of the coalition, depriving shippers of significant cost savings. In this study, we propose algorithm to design coalition structure which consist of multiple disjoint stable coalitions. Each coalition must have a minimum cost collaborative solution with an acceptable cost allocation. Due to the complexity of the task hand, we devised a heuristic to find good quality solutions to this problem