Outbound Trucks Research Articles

Truck scheduling in cross-docking terminals with fixed outbound departures

At a cross-docking terminal, inbound shipments are directly transshipped across the terminal to designated outbound trucks, so that delays and inventories are kept as low as possible. We consider an operational truck scheduling problem, where a dock door and a start time have to be assigned to each inbound truck. A set of outbound trucks is scheduled beforehand and, therefore, departure times are fixed. If a shipment is not unloaded, transshipped to the outbound gate and loaded onto the designated outbound truck before its departure, we consider the shipments's value as lost profit. The objective is to minimize total lost profit. This paper at hand formalizes the resulting truck scheduling problem. We settle its computational complexity and develop heuristics (namely, decomposition procedures and simulated annealing) in order to tackle the problem. We show the efficiency of these heuristics by means of a computational study. Last but not least, a case study is presented.

Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using GRASP method

Article history: Received 18 May 2012 Received in revised format 7 July 2012 Accepted July 31 2012 Available online 5 August 2012 Cross docking play an important role in management of supply chains where items delivered to a warehouse by inbound trucks are directly sorted out, reorganized based on customer demands, routed and loaded into outbound trucks for delivery to customers without virtually keeping them at the warehouse. If any item is held in storage, it is usually for a short time, which is normally less than 24 hours. The proposed model of this paper considers a special case of cross docking where there is temporary storage and uses GRASP technique to solve the resulted problem for some realistic test problems. In our method, we first use some heuristics as initial solutions and then improve the final solution using GRASP method. The preliminary test results indicate that the GRASP method performs better than alternative solution strategies. © 2012 Growing Science Ltd. All rights reserved

Two hybrid differential evolution algorithms for optimal inbound and outbound truck sequencing in cross docking operations

This paper studies inbound and outbound truck sequencing for cross docking operations with the objective to minimize total operation time (a.k.a. makespan) or equivalently to maximize the throughput of a cross docking system. Specifically, two major contributions are made: (i) designing two new hybrid differential evolution algorithms with better performance than the pure differential evolution algorithm that was reported to have the best performance in a recent comparative study of several metaheuristic algorithms, i.e., Arabani et al., and (ii) proposing a more realistic and efficient operational policy that leads to shorter makespan than that developed by Yu and Egbelu. The effectiveness of the proposed algorithms and policy are shown based on the results of testing 30 problems and several other related issues are also investigated and discussed.

Genetic algorithms for door-assigning and sequencing of trucks at distribution centers for the improvement of operational performance

In a supply chain, cross docking is one of the most innovative systems for improving the operational performance at distribution centers. By utilizing this cross docking system, products are delivered to the distribution center via inbound trucks and immediately sorted out. Then, products are shipped to customers via outbound trucks and thus, no inventory remains at the distribution center. In this paper, we consider the scheduling problem of inbound and outbound trucks at distribution centers. The aim is to maximize the number of products that are able to ship within a given working horizon at these centers. In this paper, a mathematical model for an optimal solution is derived and intelligent genetic algorithms are proposed. The performances of the genetic algorithms are evaluated using several randomly generated examples.

Simultaneous dock assignment and sequencing of inbound trucks under a fixed outbound truck schedule in multi-door cross docking operations

Abstract This paper studies the simultaneous dock assignment and sequencing of inbound trucks for a multi-door cross docking operation with the objective to minimize total weighted tardiness, under a fixed outbound truck departure schedule. The problem is newly formulated and solved by six different metaheuristic algorithms, which include simulated annealing, tabu search, ant colony optimization, differential evolution, and two hybrid differential-evolution algorithms. To evaluate the total weighted tardiness associated with any given inbound-truck sequence and dock assignment, an operational policy is developed. This policy is employed by every metaheuristic algorithm in searching for the optimal dock assignment and sequence. Each metaheuristic algorithm is tested with 40 problems. The major conclusions are: (1) metaheuristic is generally an effective optimization method for the subject problem; (2) population based metaheuristic algorithms are generally more effective than projection based metaheuristic algorithms; (3) proper selection of algorithmic parameters is important and more critical for projection based metaheuristic algorithms than population based algorithms; (4) the two best algorithms are ant colony optimization and hybrid differential evolution 2; among them, ACO takes less time than hybrid 2 and thus can be declared the best among all the six metaheuristic algorithms tested.

작업시간창이 주어진 크로스토킹 터미널에서 미 선적 물량 최소화를 위한 입출고 트럭 일정계획

This paper considers the inbound and outbound truck scheduling problem in a cross docking terminal. The unloading process from inbound trucks and loading process to outbound trucks are assumed to be performed within a time window. If some items are not able to be loaded to their scheduled outbound trucks within the time window, they are stored in the terminal and shipped using the truck visiting the next time window. The objective of this paper is to schedule inbound and outbound trucks to minimize the number of items unable to ship within the time window. A mathematical model for an optimal solution is derived, and a rule-based local search heuristic algorithm and genetic algorithm (GA) are proposed. The performance of the algorithms are evaluated using randomly generated several examples.

다수의 도어를 갖는 크로스도킹 터미널에서 입고와 출고를 병행하는 트럭일정계획을 위한 유전알고리즘

Cross docking is a logistics management concept in which items delivered to a terminal by inbound trucks are immediately sorted out, routed and loaded into outbound trucks for delivery to customers. Two main advantages by introducing a cross docking terminal are to consolidate multiple smaller shipment into full truck load and remove storage and order picking processes to save up logistics costs related to warehousing and transportation costs. This research considers the scheduling problem of trucks in the cross docking terminals with multi-door in an inbound and outbound dock, respectively. The trucks sequentially deal with the storage process at the one of inbound doors and the shipping process at the one of the outbound doors. A mathematical model for an optimal solution is derived, and genetic algorithms with two different chromosome representations are proposed. To verify performance of the GA algorithms, we compare the solutions of GAs with the optimal solutions and the best solution using randomly generated several examples.

A cross-docking scheduling problem with sub-population multi-objective algorithms

This paper deals with a scheduling problem of inbound and outbound trucks shipping incoming and outgoing product items into/out of a cross-docking system. We consider an instance of cross-docking systems in which more than one objective are taken into account: minimization of the total operation time (makespan) and minimization of the total lateness of outbound trucks. In order to deal with this problem, three multi-objective algorithms are developed as follows (based on the sub-population concept of evolutionary algorithms): sub-population genetic algorithm-II (SPGA-II), sub-population particle swarm optimization-II (SPPSO-II), and sub-population differential evolution algorithm-II (SPDE-II). In addition, to evaluate the performance of these algorithms, four measures are presented and compared with each other whose results will demonstrate that the SPPSO-II has better characteristics in comparison with other two algorithms.

Heuristic solutions for transshipment problems in a multiple door cross docking warehouse

Cross docking is a practice in logistics with the main operations of unloading products from an incoming truck, regrouping them with respect to their destinations and loading them directly into an outbound truck with minimum storage in between these operations. In this article, we study the transshipment scheduling problem in a multiple inbound and outbound dock configuration. The operations manager has several decisions to make: he can decide to transship products directly from inbound to an outbound truck, if an outbound truck is available; he can temporarily store certain products and have them loaded later on; or he can replace an outbound truck to facilitate direct loading. The objective is to find the best schedule of transshipment operations to minimize the sum of inventory holding and truck replacement costs. In this article, we present several heuristics to attain this objective. Numerical experiments are presented and the results are compared with the optimal solution to evaluate the performance of the heuristics.

Meta-heuristics implementation for scheduling of trucks in a cross-docking system with temporary storage

Cross-docking is an approach in inventory management which can reduce inventories, lead times and customer response time. In this strategy, products and shipments are unloaded from inbound trucks, sorted and categorized based on their characteristics, moved and loaded onto outbound trucks for delivery to demand points in a distribution network. The important fact is that, the items are stored in the inventory for a period which is primarily less than the actual time allocated to keep these items in a typical warehouse. Therefore, total cost and space requirement for inventory can be cut down. One of the most important targets in such systems is to establish coordination between the performance of inbound and outbound trucks in that these trucks can be scheduled, and the product items can be allocated to trucks effectively. This paper addresses some meta-heuristics to find the best sequence of inbound and outbound trucks, so that the objective, minimizing the total operation time called makespan, can be satisfied. Furthermore, not only the efficiency and capability of the algorithms’ parameters are assessed and analyzed by some performance measures, but also these meta-heuristics are compared with each other in order to find out the set of homogeneous algorithms among all proposed algorithms. By this analysis, it can be shown that the suitability of these meta-heuristics is quite sensible especially for the cross-docking systems with large sizes in which a high volume of inbound or outbound trucks transmit the product items.

Scheduling of Inbound and Outbound Trucks at Cross-Docks

A model is developed for both time and space scheduling of inbound and outbound trucks at a cross-dock facility under various objectives. Three different objectives in optimizing cross-dock operations are presented, and the justification for the use of these objectives is given. A linear mixed integer formulation of the problem is presented, and a restriction–approximation approach is developed and applied to determine the truck scheduling at a sample cross-dock facility. This paper also analyzes the behavior of each of the objectives and provides a comprehensive analysis of the results. Pareto and post-Pareto analyses of the multiobjective problem are presented.

Truck scheduling at zero-inventory cross docking terminals

Handling freight at cross docking terminals constitutes a complex planning task which comprises several executive steps as shipments delivered by inbound trucks are to be unloaded, sorted according to their designated destinations, moved across the dock and finally loaded onto outbound trucks for an immediate delivery elsewhere in the distribution system. To enable an efficient synchronization of inbound and outbound flows, a careful planning of operations, e.g. by computerized scheduling procedures, becomes indispensable. This work treats a special truck scheduling problem arising in the (zero-inventory) cross docks of the food industry, where strict cooling requirements forbid an intermediate storage inside the terminal, so that all products are to be instantaneously loaded onto refrigerated outbound trucks. The problem is formalized such that different operational objectives, i.e. the flow time, processing time and tardiness of outbound trucks, are minimized. To solve the resulting truck scheduling problem suited exact and heuristic solution procedures are presented.

Scheduling inbound and outbound trucks at cross docking terminals

At cross docking terminals, shipments from inbound trucks are unloaded, sorted and moved to dispatch points where they are directly loaded onto outbound trucks for an immediate delivery elsewhere in the distribution system. This warehouse management concept aims at realizing economies in transportation cost by consolidating divergent shipments to full truckloads without requiring excessive inventory at the cross dock. The efficient operation of such a system requires an appropriate coordination of inbound and outbound trucks, e.g. by computerized scheduling procedures.This work introduces a base model for scheduling trucks at cross docking terminals, which relies on a set of simplifying assumptions in order to derive fundamental insights into the underlying problem’s structure, i.e. its complexity, and to develop a building block solution procedure, which might be employed to solve more complex real-world truck scheduling problems.

Scheduling of inbound and outbound trucks in cross docking systems with temporary storage

Cross docking is a warehouse management concept in which items delivered to a warehouse by inbound trucks are immediately sorted out, reorganized based on customer demands, routed and loaded into outbound trucks for delivery to customers without the items being actually held in inventory at the warehouse. If any item is held in storage, it is usually for a brief period of time that is generally less than 24 hours. This way, the turnaround times for customer orders, inventory management cost, and warehouse space requirements are reduced. One of the objectives for cross docking systems is how well the trucks can be scheduled at the dock and how the items in inbound trucks can be allocated to the outbound trucks to optimize on some measure of system performance. The objective of this research is to find the best truck docking or scheduling sequence for both inbound and outbound trucks to minimize total operation time when a temporary storage buffer to hold items temporarily is located at the shipping dock. The product assignment to trucks and the docking sequences of the inbound and outbound trucks are all determined simultaneously.

Sequencing the processing of incoming mail to match an outbound truck delivery schedule

This paper considers the problem of sequencing the processing of incoming mail in a processing and distribution center (P&DC) to match a given outbound truck delivery schedule. Mail arrives at a P&DC from local associate offices or remote P&DCs following an incoming schedule. The mail from an origin has different proportions to different destinations. For each destination, there are trucks scheduled with limited capacities. The objective of the problem is to determine the sequence in which the incoming mail should be processed so that the total unused truck capacity is minimized. Since, we are not concerned with detailed scheduling/routing decisions inside the P&DC, we treat the P&DC system as a single machine. Dispatching rules and heuristics are proposed for this single machine problem and tested via computational experiments. Simulation experiments are performed to test the efficiency of these methods for the original multi-center multi-machine system.

Use of Vessel Freight Data to Forecast Heavy Truck Movements at Seaports

Ports are primary generators of truck traffic in the United States. Seaport operations will require operational and infrastructure changes to maintain the growth of international cargo operations. Truck trip generation models will provide transportation planners and public agencies with valuable information necessary for prioritizing funds for roadway upgrade projects and port infrastructure modifications. A new methodology is presented that combines backpropagation neural networks (BPN) and time series to forecast inbound and outbound heavy truck movements at seaports. The new method uses vessel freight data to identify which parameters are relevant for use as model input in predicting truck traffic at seaports. The method is successfully applied to five ports in Florida—Miami, Tampa, Palm Beach, Jacksonville, and Everglades—thus demonstrating its transferability. Details are provided for the Port of Everglades. The commodities at this port are classified into tons, barrels, and containers. It was found that the primary factors affecting truck traffic are imported containers, imported tonnage, imported barrels, exported containers, exported tonnage, and the particular weekday of operation. Separate BPN models were developed for inbound and outbound truck traffic at the ports. The new method forecasts that the Port of Everglades will have a 33% increase in average daily inbound heavy trucks and a 30% increase in average daily outbound heavy trucks by 2005 (2000 is the base year). The accuracy of the inbound and the outbound truck models is 93% and 92%, respectively.

Truck Trip Generation Models for Seaports with Container and Trailer Operation

Freight movement throughout the United States continues to evolve as a significant challenge to the transportation industry. Seaport operations dominated by container and trailer movements will require operational and infrastructure changes to maintain the growth of international cargo operations. Transportation planning models can be used to determine the needs of port and street network modifications. Described is the research and initial development process of models for predicting the levels of cargo truck traffic moving inbound and outbound at the Port of Miami. The models were restricted to container and trailer truck configurations that transport virtually all of the Port of Miami’s freight. Consequently, this associated truck traffic moves through the nearby street network within downtown Miami. The purpose of the trip generation models is to predict volumes of large inbound and outbound trucks for specified time frames. The concern is to know how many large cargo vehicles are traveling on the only road leading to the port. Primary factors affecting truck volume were found to be the amount and direction of cargo vessel freight and the particular weekday of operation. Time series models for predicting seasonal variations in freight movements were developed as part of the study. These models are useful for long-term forecasts of the input variables used in the trip generation models. Truck trip generation models will provide transportation planners and public agencies with valuable information when making transportation management decisions and infrastructure modifications. This information also is necessary for prioritizing funds for roadway upgrade projects.

Innovative Approaches to Regional Freight Transportation Planning: Case Study of Monterey Bay Region

How a California metropolitan planning organization (MPO) overcame data limitations and developed innovative solutions to regional agricultural freight transportation problems is described. Data from government agencies and trade groups on annual fruit and vegetable production, fish landings, and wine production were combined with survey data on truck volumes and loading practices to develop novel approaches for estimating truck and rail trips. Similar methods were used to project future freight volumes by using key population, income, and agricultural productivity indexes to project agricultural production volumes and employment forecasts in the processed food industries and thereby forecast freight volumes in their industries. To identify problems and deficiencies in the system, new performance indicators such as number of internal truck trips per outbound line-haul trip, wait time per pickup, comparisons of hourly inbound and outbound line-haul truck trip distributions, and truck trips as a percent of total traffic volume on roadways with poor level of service were used. It was concluded that poor logistics planning, lack of coordinated information and communications about load availability, poor load consolidation practices, and inadequate truck parking and driver waiting facilities were among the biggest problems facing the region. A proposed freight logistics center, which may be developed as a public-private partnership, is now under consideration. The methods and programs developed in this study may have applications in other small to medium-sized MPOs.

Innovative Approaches to Regional Freight Transportation Planning: Case Study of Monterey Bay Region

How a California metropolitan planning organization (MPO) overcame data limitations and developed innovative solutions to regional agricultural freight transportation problems is described. Data from government agencies and trade groups on annual fruit and vegetable production, fish landings, and wine production were combined with survey data on truck volumes and loading practices to develop novel approaches for estimating truck and rail trips. Similar methods were used to project future freight volumes by using key population, income, and agricultural productivity indexes to project agricultural production volumes and employment forecasts in the processed food industries and thereby forecast freight volumes in their industries. To identify problems and deficiencies in the system, new performance indicators such as number of internal truck trips per outbound line-haul trip, wait time per pickup, comparisons of hourly inbound and outbound line-haul truck trip distributions, and truck trips as a percent of total traffic volume on roadways with poor level of service were used. It was concluded that poor logistics planning, lack of coordinated information and communications about load availability, poor load consolidation practices, and inadequate truck parking and driver waiting facilities were among the biggest problems facing the region. A proposed freight logistics center, which may be developed as a public-private partnership, is now under consideration. The methods and programs developed in this study may have applications in other small to medium-sized MPOs.