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.     

A bounded dynamic programming approach to schedule operations in a cross docking platform

Cross docking is a logistic technique employed to reduce the inventory holding, order picking, transportation costs as well as the delivery time. Products arriving to the cross dock are unloaded from inbound trailers, possibly reconsolidated with other products arriving from different destinations and loaded into outbound trailers within less than 24 h. In this study, we consider a multiple receiving and shipping door cross dock environment. The objective is to find optimal (for reasonably small cross docks) or near optimal (for larger cross docking facilities) scheduling policies which minimizes the total costs related to the transshipment operations at the facility.     

Scheduling trucks in cross docking systems with temporary storage and repetitive pattern for shipping trucks

Cross docking is a logistic concept in which product items are unloaded from inbound trucks into a warehouse and then are sorted out based on customer demands and loaded into outbound trucks. For a dock holding pattern for outbound trucks, two possible scenarios can be defined. In the first scenario, whenever a truck goes into a shipping dock, it does not leave the dock until all needed product items are loaded into outbound truck. In the second scenario, outbound trucks can enter and leave the dock repeatedly. Therefore, in the second scenario it is possible that an outbound truck loads some of its needed products from shipping dock, leaves the dock for another outbound truck, waits and goes into the shipping dock again to load all or part of its remaining product items. This paper proposes a genetic algorithm-based framework for scheduling inbound and outbound trucks in cross docking systems with temporary storage of product items at shipping dock for the second defined scenario such that minimizes total operation time. In order to show the merit of the proposed method in providing a sequence that minimizes the total operation time, the operation time of the proposed method is compared to a well-known existing model by several numerical examples. The numerical results show the high performance of the proposed algorithm.     

Optimizing truck sequencing and truck dock assignment in a cross docking system

Cross docking plays a very importation role in supply chain management. The efficiency of cross docking will influence the lead time, inventory level and response time to the customer. This research aims to improve the efficiency of multi-door cross docking by optimizing both inbound and outbound truck sequencing and both inbound and outbound truck dock assignment. The objective is to minimize the makespan. The problem is new in the literature and no previous formulation of the problem can be found. In order to optimize the problem, a model for calculating the makespan is proposed. When given a sequence of all inbound and outbound trucks, the calculation model can assign all inbound and outbound trucks to all inbound and outbound doors based on first come first served and then calculate the makespan. The proposed makespan calculation model is then integrated with a variable neighborhood search (VNS) which can optimize the sequence of all inbound and outbound trucks. Four simulated Annealing (SA) algorithms are adopted for comparison. The experimental results show the proposed VNS provides 8.23–40.97% improvement over the solution generated randomly. Although it does not provide the best result for all problems when compared with SA algorithms, it provides robust results within a reasonable time. Thus the proposed method is efficient and effective in solving cross docking operation problems.     

Crossdock truck scheduling with time windows: earliness,tardiness and storage policies

This article proposes to simultaneously plan inbound and outbound truck arrivals and departures in a cross-docking platform, as well as the internal pallet handling. The objective is to minimize both the total number of pallets put in storage and the dissatisfaction of the transportation providers, by creating a truck schedule as close as possible to the wished schedule they communicate in advance. The problem is modeled with an integer program tested on generated instances to assess its performance, especially regarding the computation time. The problem is proven to be np-hard in the strong sense. Since the execution takes too long to be used on a daily basis by platform managers, three heuristics are also proposed and tested. Two are based on integer programs solved sequentially, the third one is a tabu search in which the storage part of the objective function is evaluated by a maximum flow model in a graph. Numerical experiments show in which conditions each heuristic performs best, which can help choosing a solution method when confronted to a real-life problem.     

A tabu search approach to the truck scheduling problem with multiple docks and time windows

While organizing the cross-docking operations, cross-dock managers are confronted with many decision problems. One of these problems is the truck scheduling problem. This paper presents a truck scheduling problem that is concerned with both inbound and outbound trucks at multiple dock doors. The objective is to minimize the total travel time and the total tardiness. The truck scheduling problem under study is described in detail and a mathematical model of the problem is provided which can be solved to optimality with a mixed integer programming solver, at the expense of a high computation time. Next, a tabu search approach is presented. Experimental results on new benchmark instances indicate that the proposed tabu search is able to find good quality results in a short time period, thus offering potential for integration in cross-docking decision support systems.     

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.     

多模式自动化存取系统设备调度与任务分配

多模式自动化存取系统是一种新型仓储系统,其存储空间利用率高、设备配置灵活.为提高作业效率,降低运行成本,需对系统进行设备调度和任务分配,实现按需配置和管理系统资源.通过将系统的作业过程建模为多个服务中心组成的排队网络,对服务中心设备数量进行调度,保证系统稳态运行.基于预期作业时间设计具有两级模糊规则的模糊控制器,为托盘物资上下架任务分配托盘提升机,实现托盘物资上下架任务的优化分配,减少作业过程所需的运输路径,从而提高作业效率,减少作业叉车数量,降低作业成本.文中通过一个托盘物资上架任务仿真算例,验证了模糊控制任务分配策略的有效性.     

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.     

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.     

Post disaster adaptation management in airport: A coordination of runway and hangar resources for relief cargo transports

Air traffic congestions for processing relief cargos under post-disaster relief scenarios are common, due to high transport demands within a short time. To enhance the resilience of relief operations at airport, an optimization problem of relief air cargo transportations involving aircraft sequencing and loading/unloading within a designated hangar is studied in this paper. The objective is minimizing the tardiness in fulfilling inbound and outbound relief cargos. A mixed-integer linear programming model is formulated, which incorporates aircraft sequencing and hangar parking planning. To resolve the practical problem efficiently, we propose a two-stage optimization approach, which reduces complexity in solving the original model by coordinating the decisions of aircraft landing and take-off schedule and cargo hangar parking arrangement through iterations. The efficiency of the proposed method is examined through the computational results. High-quality solutions can be obtained by the two-stage optimization method within a reasonable time for practical implementation, which enhances the responsiveness and resource utilization of airport operations management under disaster relief situations.     

Exploring mathematical approximation for the time spans of transfer operations in parcel transshipment terminals

The parcel delivery industry (PDI) is a very labor intensive industry, from the drivers of the pickup and delivery vans, to the unloaders, sorters, and loaders in the transshipment terminals. The labor efficiency is a key performance measure in the PDI. In this study, the focus is on developing a framework for improving labor efficiencies in a parcel transshipment terminal. The objective is to minimize the time required to transfer parcels from inbound trailers to outbound trailers. This paper is an exploratory study to developing a framework for a solution approach to solve large-scale parcel hub scheduling problems (PHSP). A binary integer programming (BIP) model is proposed along with a branch and bound (BaB) algorithm with lower and upper bounds. The computational study shows that the BaB algorithm is able to generate solutions for small-size problems. The proposed BIP model sets the ground work for developing solution approaches to much larger size problems.     

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.     

Genetic-based scheduling to solve the parcel hub scheduling problem

The parcel hub scheduling problem (PHSP) is scheduling problem that is common in the parcel delivery industry. The PHSP consists of scheduling a set of inbound trailers containing a batch of heterogeneous parcels to a set of unload docks with the objective of minimizing the time span of the transfer operation. The transfer operation involves unloading the inbound trailers and sorting and loading the parcels onto outbound trailers. The unload schedule can have a significant impact on the amount of time required to complete the transfer operation. In this paper, a mathematical model is proposed to solve small-size problems and a genetic algorithm is presented to solve the large-size problems with minimum computational time compared to other competing approaches.     

The petrol station replenishment problem with time windows

In the Petrol Station Replenishment Problem with Time Windows (PSRPTW) the aim is to optimize the delivery of several petroleum products to a set of petrol stations using a limited heterogeneous fleet of tank-trucks. More specifically, one must determine the quantity of each product to deliver, the assignment of products to truck compartments, delivery routes, and schedules. The objective is to maximize the total profit equal to the sales revenue, minus the sum of routing costs and of regular and overtime costs. This article first proposes a mathematical formulation of the PSRPTW. It then describes two heuristics based on arc preselection and on route preselection. Extensive computational tests on randomly generated instances confirm the efficiency of the proposed heuristics. Finally, a performance analysis on a real case shows a distance reduction of more than 20% over a solution obtained by an experienced dispatcher.     

Scheduling cross docking operations under full,partial and no information on inbound arrivals

Cross docking is a logistic technique which seeks to reduce the inventory holding, order picking, transportation costs and delivery time. Little attention has been given to the transshipment operations inside a cross dock. In this article, we study the transshipment scheduling problem in a single receiving and a single shipping door cross dock under three scheduling policies: In the first policy, we assume to have complete information on the order of arrivals and the contents of all inbound trucks. The second and the third policies assume the availability of partial and no information on the sequence of upcoming trucks. An optimal graph based model is proposed for the full information case, and a polynomial time algorithm is given. Heuristics are developed for the other two cases. The comparison of the costs associated to each policy helps evaluating the value of information in cross dock scheduling problems.     

Integrating carrier selection with supplier selection decisions to improve supply chain security

Supply chain security is a major concern for logistics managers who have responsibility for inbound and outbound shipments to and from both domestic and international locations. We propose here that logistics decisions concerning security in the supply chain will be made more effectively when made in concert with decisions in related supply chain processes, especially supplier and carrier selection. Indeed, managers may minimize cost, transit time, and security risk by integrating decision processes internally, as well as with their carrier's and supplier's operations. Thus, we account for both intra‐firm collaboration between logistics and purchasing managers, as well as inter‐firm collaboration among buyers, suppliers, and carriers in a supply chain. In this paper, we propose a decision process that features a set of security rules and a multi‐objective optimization model to accomplish this aim. We then provide an illustration to demonstrate the potential usefulness of these concepts in practice.     

A GRASP with adaptive large neighborhood search for pickup and delivery problems with transshipment

The pickup and delivery problem (PDP) has been studied extensively for applications ranging from courier, cargo and postal services, to public transportation. The work presented here was inspired by a daily route planning problem at a regional air carrier who was trying to determine the benefits of transshipment. Accordingly, a primary goal of this paper is identify the circumstances under which measurable cost saving can be achieved when one aircraft transports a request from its origin to an intermediate point and a second aircraft picks it up and delivers it to its final destination. In structuring the analysis, we describe a unique way to model this transshipment option on a directed graph and introduce a specialized two-route insertion heuristic that considers when to exploit this option. Based on the new representation, most existing heuristics for the PDP can be readily extended to handle transshipments.To find solutions, we developed a greedy randomized adaptive search procedure (GRASP) with several novel features. In the construction phase, shipment requests are inserted into routes until all demand is satisfied or no feasible insertion exists. In the improvement phase, an adaptive large neighborhood search algorithm is used to modify portions of the feasible routes. Specialized removal and insertion heuristics were designed for this purpose. In the absence of test cases in the literature, we also developed a procedure for randomly generating problem instances. Testing was done on 56 existing PDP instances which have 50 requests each, and on 50 new data sets with 25 requests each and one transshipment location. For the former, the performance and solution quality of the GRASP were comparable to the best known heuristics. For the latter, GRASP found the solutions within 1% of optimality on 88% of the instances.     

Multi-route railroad blocking problem by improved model and ant colony algorithm in real world

In rail freight transportation, general merchandise freight cars may pass through many classification stations on their route from origin to destination. The Railroad Blocking Problem (RBP) is to reclassify inbound traffic from various origins in the classification stations and put them on outbound trains with the same or close destinations, the objective of the RBP is to minimize the total operating costs of delivering all traffic on the railway network while satisfying the resource and capacity constraints at the stations and the priority constraints for shipments. In this paper, we introduce a new mathematic model which can comprehensively describe the blocking strategy and various combinations of multi-route O–D pairs in large scale railway network. Furthermore, we propose an improved Ant Colony (AC) algorithm for RPB, and a computational experiment derived from the real life instances of coal heavy haul rail network in north China is given. Experimental results verified the validation of the model and effectiveness of the algorithm.     

A simulation modeling and analysis for RFID-enabled mixed-product loading strategy for outbound logistics: A case study

Loading of trucks in a plant can be a problem when different kinds of products are to be loaded on the same truck, but these goods are not ready. Therefore, the truck has to wait at the loading bay for an unbearably long time, blocking other trucks also in the process. In this paper we address this problem and present several alternative strategies for drawing loading schedules in such situations, using information on status of products obtained with radio-frequency identification (RFID) technology, and compare their performance with traditional strategies, without RFID. A case study on a giant printing and paper bag manufacturer is conducted. Simulation models under these strategies are built for comparisons with respect to three performance measures: average operating time in system, throughput of trucks and percentage of tardy performance trucks. Results demonstrate that these strategies have different performances with respect to different criteria.