Direct Shipment Research Articles

An adaptive structure of a hub-and-spoke system with direct and depot shipments in the case of volatile demand over time

The classical logistic structure for a group age delivery system in a defined geographic region is often created by a hub-and-spoke system consisting of depots, service areas of the depots, routes for each depot from and to the customers in the service area, and a line haul design. The hub-and-spoke structure is fixed as part of strategic planning. Due to the long planning horizon of strategic planning it is often difficult to predict demand over time. Operating a certain hub-and-spoke system in case of highly variable demand during the life cycle can result in inefficiency of the transportation system. In this paper an adaptive planning system is developed that can rearrange the service areas and the depots as well as the trans-loading points between line haul and local tours of the service areas and determine new vehicle routes. Our hub-and-spoke system also allows direct service from the hub to a single customer. The re-optimization of the hub-and-spoke system is based on a solution of a multi-depot variable service areas vehicle routing problem (MD-VSA-VRP). The problem is NP-hard. In this paper we present a mixed integer linear program and a metaheuristic solution concept. Further, we show via case studies the applicability of the new planning model.

Carbon Reduction Investments under Direct Shipment Strategy

Recently much research efforts have focused on how to manage carbon emissions in logistics operations. This paper formulates a model to determine an optimal shipment size with aims to minimize the total cost consisting not only of inventory and transportation costs but also cost for carbon emissions. Unlike the literature assuming carbon emission factors as a given condition, we consider the emission factors as decision variables. It is allowed to make an investment in improving carbon emission factors. The optimal investment decision is shown to be of a threshold type with respect to unit investment costs. Moreover, the findings in this work provide insights on the various elements of the investment decision and their impacts.

A novel learning based approach for a new integrated location-routing and scheduling problem within cross-docking considering direct shipment

One of the most important problem in supply chain management is the design of distribution systems which can reduce the transportation costs and meet the customer's demand at the minimum time. In recent years, cross-docking (CD) centers have been considered as the place that reduces the transportation and inventory costs. Meanwhile, neglecting the optimum location of the centers and the optimum routing and scheduling of the vehicles mislead the optimization process to local optima. Accordingly, in this research, the integrated vehicle routing and scheduling problem in cross-docking systems is modeled. In this new model, the direct shipment from the manufacturers to the customers is also included. Besides, the vehicles are assigned to the cross-dock doors with lower cost. Next, to solve the model, a novel machine-learning-based heuristic method (MLBM) is developed, in which the customers, manufacturers and locations of the cross-docking centers are grouped through a bi-clustering approach. In fact, the MLBM is a filter based learning method that has three stages including customer clustering through a modified bi-clustering method, sub-problems’ modeling and solving the whole model. In addition, for solving the scheduling problem of vehicles in cross-docking system, this paper proposes exact solution as well as genetic algorithm (GA). GA is also adapted for large-scale problems in which exact methods are not efficient. Furthermore, the parameters of the proposed GA are tuned via the Taguchi method. Finally, for validating the proposed model, several benchmark problems from literature are selected and modified according to new introduced assumptions in the base models. Different statistical analysis methods are implemented to assess the performance of the proposed algorithms.

ConnectomeDB—Sharing human brain connectivity data

ConnectomeDB is a database for housing and disseminating data about human brain structure, function, and connectivity, along with associated behavioral and demographic data. It is the main archive and dissemination platform for data collected under the WU-Minn consortium Human Connectome Project. Additional connectome-style study data is and will be made available in the database under current and future projects, including the Connectome Coordination Facility. The database currently includes multiple modalities of magnetic resonance imaging (MRI) and magnetoencephalograpy (MEG) data along with associated behavioral data. MRI modalities include structural, task, resting state and diffusion. MEG modalities include resting state and task. Imaging data includes unprocessed, minimally preprocessed and analysis data. Imaging data and much of the behavioral data are publicly available, subject to acceptance of data use terms, while access to some sensitive behavioral data is restricted to qualified investigators under a more stringent set of terms. ConnectomeDB is the public side of the WU-Minn HCP database platform. As such, it is geared towards public distribution, with a web-based user interface designed to guide users to the optimal set of data for their needs and a robust backend mechanism based on the commercial Aspera fasp service to enable high speed downloads. HCP data is also available via direct shipment of hard drives and Amazon S3.

Evolving competition between Hong Kong and Shenzhen ports

Shenzhen Port (SZP), once a negligible local port, has risen dramatically to a world-leading container port and an “equal” player with Hong Kong Port (HKP). Will this market share reallocation continue, or will equilibrium be eventually realized for HKP to prosper continuously? We examine the relationship between these two ports to answer this question. We propose a new transformation method to describe the growth of container cargo transport demand, define the quantitative measures of the competition relationship and port competitiveness, and present a rigorous analytical framework with econometric tests and models to understand the true relationship between HKP and SZP. Direct empirical tests suggest that SZP complements HKP; however, the two ports exhibit strong competition when the effect of demand growth is excluded. Considering transshipment separately, we find that the impact of SZP on HKP is negative in transshipment but complementary in direct shipment. We may conclude that HKP does not affect SZP, whereas SZP has competitive power over HKP. These results are consistent with the findings of some previous theoretical studies.

A Flexible Integrated Forward/ Reverse Logistics Model with Random Path-based Memetic Algorithm

Due to business and environmental issues, the efficient design of an integrated forward/reverse logistics network has recently attracted more attention from researchers. The significance of transportation cost and customer satisfaction spurs an interest in developing a flexible network design model with different delivery paths. This paper proposes a flexible mixed-integer programming model to deal with such issues. The model integrates the network design decisions in both forward and backward logistics networks, and also applies three kinds of delivering modes (normal delivery, direct shipment, and direct delivery) which enrich the model to be able to deliver the products to customers by distribution-skipping the mid-process strategy in order to deliver products in more flexible paths to customer zones. To tackle with such an NP-hard problem, a memetic algorithm (MA) with random path-based direct representation and combinatorial local search methods is developed. Numerical experiments are conducted to demonstrate the significance and applicability of the model as well as the efficiency and accuracy of the proposed solution approach.

Bi-objective integrating sustainable order allocation and sustainable supply chain network strategic design with stochastic demand using a novel robust hybrid multi-objective metaheuristic

Sustainability has been considered as a growing concern in supply chain network design (SCND) and in the order allocation problem (OAP). Accordingly, there still exists a gap in the quantitative modeling of sustainable SCND that consists of OAP. In this article, we cover this gap through simultaneously considering the sustainable OAP in the sustainable SCND as a strategic decision. The proposed supply chain network is composed of five echelons including suppliers classified in different classes, plants, distribution centers that dispatch products via two different ways, direct shipment, and cross-docks, to satisfy stochastic demand received from a set of retailers. The problem has been mathematically formulated as a multi-objective optimization model that aims at minimizing the total costs and environmental effect of integrating SCND and OAP, simultaneously. To tackle the addressed problem, a novel multi-objective hybrid approach called MOHEV with two strategies for its best particle selection procedure (BPSP), minimum distance, and crowding distance is proposed. MOHEV is constructed through hybridization of two multi-objective algorithms, namely the adapted multi-objective electromagnetism mechanism algorithm (AMOEMA) and adapted multi-objective variable neighborhood search (AMOVNS). According to achieved results, MOHEV achieves better solutions compared with the others, and also crowding distance method for BPSP outperforms minimum distance. Finally, a case study for an automobile industry is used to demonstrate the applicability of the approach.

Hub-and-spoke logistics network design for third party logistics service providers

Third Party Logistics service providers (3PLs) are playing an increasing role in the management of supply chains. 3PLs offer a wide range of logistics services, e.g. warehousing and transportation services. We consider a 3PL company that is responsible for managing the inbound logistics of raw materials and components from multiple suppliers to several manufacturing plants. In this paper, we consider the hub-and-spoke logistics network design problem for 3PL companies. Our purpose is to decide on the number, location and operation of hub facilities so as to minimize the total logistics costs for the network. We formulate the problem as a mixed integer nonlinear programming model and linearize it using a step-by-step approach. Linearization of the model makes it possible to solve it to optimality using a standard optimization package. Numerical results reveal substantial cost saving as a consequence of using the hub-and-spoke network configuration compared to a direct shipment strategy.

The time-dependent two-echelon capacitated vehicle routing problem with environmental considerations

Multi-echelon distribution strategy in which freight is delivered to customers via intermediate depots rather than using direct shipments is an increasingly popular strategy in urban logistics. This is primarily to alleviate the environmental (e.g., energy usage and congestion) and social (e.g., traffic-related air pollution, accidents and noise) consequences of logistics operations. This paper presents a comprehensive MILP formulation for a time-dependent two-echelon capacitated vehicle routing problem (2E-CVRP) that accounts for vehicle type, traveled distance, vehicle speed, load, multiple time zones and emissions. A case study in a supermarket chain operating in the Netherlands shows the applicability of the model to a real-life problem. Several versions of the model, each differing with respect to the objective function, are tested to produce a number of selected key performance indicators (KPIs) relevant to distance, time, fuel consumption and cost. The paper offers insight on economies of environmentally friendly vehicle routing in two-echelon distribution systems. The results suggest that an environmentally friendly solution is obtained from the use of a two-echelon distribution system, whereas a single-echelon distribution system provides the least-cost solution.

Regulation and Contract Choice in the Distribution of Wine

The wine industry in the United States has grown tremendously over the past few decades, from fewer than 1,000 wineries in 1980 to upward of 8,500 today. The growth has occurred over a period that has seen substantial changes in the structure of the wine industry, the modes of distribution available to wineries, and the regulations governing them. Most economic research, however, has focused on supply relations between wineries and wine grape growers rather than between wineries and their downstream markets. In this article, we examine wineries’ contracting behavior with downstream distributors and the effects of industry structure, winery organizational structure, and state laws regarding direct shipment and distribution franchise laws.

Optimization Model and Algorithm for Responsive Closed-Loop Supply Chain Logistics Network with Direct Shipment under E-Commerce

In view of the characteristic of goods return in electronic commerce which some returned goods can be redistributed directly to customers after handling simply, a responsive closed-loop supply chain logistics network with integrating forward and reverse flow is researched. The returning feature of online commodity and economy of scale of return goods at initial collection point are based, and the optimization design model of closed-loop supply chain network aiming at determining the number and location of hybrid centers and initial collection points is presented, and a hybrid genetic algorithm is devised to solve the closed-loop supply chain logistics network problem. The usefulness of the proposed model and algorithm is validated by its application to an illustrative example.

Cross-docking and milk run logistics in a consolidation network: A hybrid of harmony search and simulated annealing approach

In this paper, we develop a novel integer programming model for the transportation problem of a consolidation network where a set of vehicles are used to transport goods from suppliers to their corresponding customers via three transportation systems: direct shipment, shipment through cross-dock (indirect shipment) and milk run. Since the proposed problem formulation is NP-hard, we offer a hybrid of harmony search (HS) and simulated annealing (SA) based heuristics (HS-SA algorithm) in order to solve the problem. The objective of this problem is to minimize the total shipping cost in the network, so it is tried to reduce the number of required vehicles using an efficient vehicle routing strategy in the algorithm. Solving several numerical examples demonstrates that our solving approach performs much better than GAMS/CPLEX in reducing both the shipping cost in the network and computational time requirement, especially for large size problem instances.

Bi-objective supply chain planning in a fuzzy environment

This paper proposes a fuzzy bi-objective mixed integer linear programming formulation and solution methodology for a multi-echelon, multi-product and multi-period supply chain planning. The supply chain is a network of suppliers, plants, distribution centers, cross-docks and retailers. Products are delivered to retailers through cross-docks or directly from manufacturing plants. Cross-docking as an efficient logistic strategy is an intermediate level that involves receiving products from various resources distribution centers, sorting and then shipping them to their destinations retailers. The aim of this paper is to present a model that minimizes the total cost and develops a just-in-time JIT distribution for the supply chain. The proposed model integrates procurement, production and distribution plans in the tactical level under fuzzy supply, production and demand by considering cross-docking and direct shipments simultaneously. Triangular fuzzy numbers are adapted to represent fuzzy parameters. Moreover, the fuzzy chance-constrained programming is applied to transform the fuzzy model into an auxiliary crisp model.

Harmony search optimization algorithm for a novel transportation problem in a consolidation network

This article presents a new harmony search optimization algorithm to solve a novel integer programming model developed for a consolidation network. In this network, a set of vehicles is used to transport goods from suppliers to their corresponding customers via two transportation systems: direct shipment and milk run logistics. The objective of this problem is to minimize the total shipping cost in the network, so it tries to reduce the number of required vehicles using an efficient vehicle routing strategy in the solution approach. Solving several numerical examples confirms that the proposed solution approach based on the harmony search algorithm performs much better than CPLEX in reducing both the shipping cost in the network and computational time requirement, especially for realistic size problem instances.

Benefits of in-vehicle consolidation in less than truckload freight transportation operations

Researchers and public agencies have proposed consolidation policies as an alternative to increase truck payload utilization and mitigate externalities produced by freight transportation. Understanding and enhancing the economic mechanisms that lead to freight consolidation can ease the implementation of these strategies, increase profits for shippers and carriers, and reduce freight-related negative externalities. An important mechanism that has recently been studied for cost reduction in the freight industry is combinatorial auctions. In these auctions, a shipper invites a set of carriers to submit bids for freight lane contracts. Carriers can bid for individual lanes or bundles of them according to their operational characteristics. These bids are constructed considering direct shipments (Truckload operations) and several biding advisory models have been proposed for this purpose. However, there are economies of scale that can be achieved if shipments are consolidated inside vehicles, which have not been explored in the construction of competitive bids. This paper investigates such benefits and provides insights on the competitiveness and challenges associated to the development of consolidated bids (suitable for Less-Than-Truckload operations). Consolidated bids are constructed using a multi-commodity one-to-one pickup-and-delivery vehicle routing problem that is solved using a branch-and-price algorithm. The numerical experiment shows that non-consolidated bids are dominated by consolidated bids, which implies that this type of operation can increase the likelihood of a carrier to win auctioned lanes, while increasing its profits margins over truckload companies (non-consolidated bids), and keeping the reported benefits that combinatorial auctions represent for shippers.

Truck capacity analysis in a cross‐dock transportation network considering direct shipment

SUMMARYIn a transportation network, decision making parameters may change and may cause the optimum value of objective function to vary in a specific range. Therefore, managers try to identify the effects of these changes by sensitive analysis to find appropriate solutions. In this paper, first, a model for cross‐dock transportation network considering direct shipment is presented, and then an algorithm based on branch and bound algorithm and dual price concept for sensitive analysis is developed. When managers encounter problems such as budget limit, they may decide to change the capacity of trucks as a procedure to reduce the transportation costs of the network. The algorithm provides a useful lower bound on the solutions of the problems and makes it easy for the managers to eliminate inappropriate options of truck capacities, which cannot lead to cost reduction. To verify the algorithm, an example will be given at the end of the paper. Copyright © 2013 John Wiley & Sons, Ltd.

Multi-commodity warehouse location and distribution planning with inventory consideration

We consider the problem of designing a distribution network for a logistics provider that acquires products from multiple facilities and then delivers those products to many retail outlets. Potential locations for consolidation facilities that combine shipments for cost reduction and service improvements are considered. The problem is formulated with direct shipment and consolidation opportunities. A novel mathematical model is derived to solve a complex facility location problem determining: (i) the location and capacity level of warehouses to open; (ii) the distribution route from each production facility to each retailer outlet; and (iii) the quantity of products stocked at each warehouse and retailer. A genetic algorithm and a specific problem heuristic are designed, tested and compared on several realistic scenarios.

Benefits of in-Vehicle Consolidation in Less than Truckload Freight Transportation Operations

Researchers and public agencies have proposed consolidation policies as an alternative to increase truck payload utilization and mitigate externalities produced by freight transportation. Understanding and enhancing the economic mechanisms that lead to freight consolidation can ease the implementation of these strategies, increase profits for shippers and carriers, and reduce freight-related negative externalities. An important mechanism that has recently been studied for cost reduction in the freight industry is combinatorial auctions. In these auctions, a shipper invites a set of carriers to submit bids for freight lane contracts. Carriers can bid for individual lanes or bundles of them according to their operational characteristics. These bids are constructed considering direct shipments (Truckload operations) and several biding advisory models have been proposed for this purpose. However, there are economies of scale that can be achieved if shipments are consolidated inside vehicles, which have not been explored in the construction of competitive bids. This paper investigates such benefits and provides insights on the competitiveness and challenges associated to the development of consolidated bids (suitable for Less-than-Truckload operations). Consolidated bids are constructed using a multi-commodity one-to-one pickup-and-delivery vehicle routing problem that is solved using a branch-and-price algorithm. The numerical experiment shows that non-consolidated bids are dominated by consolidated bids, which implies that this type of operation can increase the likelihood of a carrier to win auctioned lanes, while increasing its profits margins over truckload companies (non-consolidated bids), and keeping the reported benefits that combinatorial auctions represent for shippers.

Price Effects and the Commerce Clause: The Case of State Wine Shipping Laws

In the wake of Granholm v. Heald, numerous states passed new laws to regulate interstate direct shipment of alcohol that would seem to contradict the spirit, if not the explicit content, of the Commerce Clause. We build on existing scholarship analyzing the empirical impacts of direct shipment barriers to identify how these new laws are likely to influence local market conditions. Drawing on new data that measure posted winery prices and aggregate production levels in 2002 and 2004, we demonstrate how many of these new laws would be expected to effectively diminish, if not altogether remove, the benefits that would normally accrue to consumers from legalized interstate direct shipment of wine. Although empirical analysis of price effects currently plays a very limited role in dormant Commerce Clause cases, our analysis suggests how price data can be used to ascertain whether a state restriction constitutes discrimination against out‐of‐state economic interests.

Planning of Production, Inventory and Logistics with Direct Shipment and Milk run Strategies: Numerical Experiment

We study a supply chain comprised of a manufacturer owning multiple production lines and a warehouse, and multiple retailers buying from the manufacturer. The manufacturer can choose whether to send products to the retailers directly from loading area using direct shipment or send the product to be stored at the warehouse. If the demand is satisfied from the warehouse, the company can choose the logistic strategy. The company can send the product from the warehouse to a retailer using a direct shipment mode (a truck only visits the retailer) or using milk run mode (a truck visits multiple retailers in a single trip). We develop a mixed integer programming model to find the optimal decisions for production quantities at each production line, the quantities of inventories at the loading area, the warehouse and the retailers, and the transportation strategies to deliver products to retailers in every period. We conduct numerical experiments and then analyze the results. Many managerial insights are drawn for practitioners. Several optimal transportation strategies are observed by mixing between a temporal demand aggregation strategy, the milk run strategy and the direct shipment strategy.