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.     

A novel dynamic genetic algorithm-based method for vehicle scheduling in cross docking systems with frequent unloading operation

An important factor for efficiently managing the supply chain is to efficiently control the physical flow of the supply chain. For this purpose, many companies try to use efficient methods to increase customer satisfaction and reduce costs. Cross docking is a good method to reduce the warehouse space requirements, inventory management costs, and turnaround times for customer orders. This paper proposes a novel dynamic genetic algorithm-based method for scheduling vehicles in cross docking systems such that the total operation time is minimized. In this paper, it is assumed that a temporary storage is placed at the shipping dock and inbound vehicles are allowed to repeatedly enter and leave the dock to unload their products. In the proposed method of this paper two different kinds of chromosome for inbound and outbound trucks are proposed. In addition, some algorithms are proposed including initialization, operational time calculation, crossover and mutation for inbound and outbound trucks, independently. Moreover a dynamic approach is proposed for performing crossover and mutation operation in genetic algorithm. In order to evaluate the performance of the proposed algorithm of this paper, various examples are provided and analyzed. The computational results reveal that the proposed algorithm of this paper performs better than two well-known works of literature in providing solutions with shorter operation time.     

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.     

萤火虫群优化算法在越库调度问题中的应用

萤火虫群优化算法是一种新兴的群体智能优化算法,目前在组合优化领域中的应用比较少。提出萤火虫群优化算法（Glowworm Swarm Optimization,GSO）求解越库调度问题的优化方法。越库调度问题是一类极为复杂的NP难题,是影响越库配送效率的关键问题。依据算法和问题特点,设计基于随机键的两段式最大顺序值编码方法。为了解决GSO算法优化精度低、收敛速度慢等问题,提出逐维移动,贪婪接受的搜索策略。基于社会心理学原理,对位置更新公式进行改进。通过实验仿真,结果表明改进的GSO算法是求解越库调度问题的有效方法。     

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.     

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.     

Single-coordinate-driving method for molecular docking: application to modeling of guest inclusion in cyclodextrin

An extension of the computer program CICADA has been developed that allows us to use the single-coordinate-driving (SCD) method for flexible molecular docking. The docking procedure is composed of three independent space rotations, three independent translations, and the torsions selected by the user. One of the coordinates is driven; the other coordinates are relaxed. This procedure follows low-energy wells on the potential energy surface of the entire system. The program allows us to dock more than one ligand molecule to the receptor. We ran two test examples, docking N,N-dimethylformamide into alpha-cyclodextrin and R-phenoxypropionic acid into beta-cyclodextrin. The test examples showed that the SCD approach is able to overcome high-energy barriers and to cover the entire box within which the search is performed. The limitations of molecular dynamics docking in comparison with our approach also are discussed. The philosophy of the newly developed approach is not only to find the best dock for the receptor-ligand(s) system, but also to describe all the important binding modes and provide a good starting point for studying the dynamics within the cavity during the docking process.     

The Pickup and Delivery Problem with Cross-Docking

Usual models that deal with the integration of vehicle routing and cross-docking operations impose that every vehicle must stop at the dock even if the vehicle collects and delivers the same set of goods. In order to allow vehicles to avoid the stop at the dock and thus, reduce transportation costs, we introduce the Pickup and Delivery Problem with Cross-Docking (PDPCD). An Integer Programming formulation and a Branch-and-price algorithm for the problem are discussed. Our computational results indicate that optimal or near optimal solutions for PDPCD indeed allow total costs to be significantly reduced. Due to improvements in the resolution of the pricing problems, the Branch-and-price algorithm for PDPCD works better than similar algorithms for other models in the literature.     

Roboat III: An autonomous surface vessel for urban transportation

In this paper, we present our novel autonomous surface vessel platform, a full-scale Roboat for urban transportation. This 4-m-long Roboat is designed with six seats and can carry a payload of up to 1000 kg. Roboat has two main thrusters for cruising and two tunnel thrusters to accommodate docking and interconnectivity between Roboats. We build an adaptive nonlinear model predictive controller for trajectory tracking to account for payload changes while transporting passengers. We use a sparse directed graph to represent the canal topological map and then find the most time-efficient global path in a city-scale environment using the $A^{*}$ algorithm. We then employ a multiobjective algorithm's lexicographic search to generate an obstacle-free path using a point-cloud projected two-dimensional occupancy grid map. We also develop a docking mechanism to allow Roboat to “grasp” the docking station. Extensive experiments in Amsterdam waterways demonstrate that Roboat can (1) successfully track the optimal trajectories generated by the planner with varying numbers of passengers on board; (2) autonomously dock to the station without human intervention; (3) execute an autonomous water taxi task where it docks to pick up passengers, drive passengers to the destination while planning its path to avoid obstacles, and finally dock to drop off passengers.     

码头装卸服务G／M／1排队模型及仿真研究

研究码头装卸仿真服务系统,M/M/1排队模型有严格的理论条件,在工程应用中对不满足理论条件的情况,模型分析结果的准确性会受到影响。为提高控制序列的准确性,提出了等间隔到达和随机到达的混合序列到达时间间隔概率分布,假定该混合到达顾客到达时间间隔相互独立同分布,采用G/M/1排队模型得出了排队服务系统的系统参数。编写MAT-LAB仿真程序,结合实例比较了G/M/1与M/M/1模型分析结果和仿真结果,表明比M/M/1模型能更准确地描述系统的各项参数,结果证明可为排队系统设计提供参考依据。     

Robust door assignment in less-than-truckload terminals

The assignment of incoming trailers to strip doors is one of the critical decisions that affect the performance of cross docking operations in less-than-truckload terminals. This paper introduces a mixed integer quadratic model with the objective of generating trailer-to-door assignments that equally distribute idle times at doors to accommodate operational level uncertainty encountered in truck arrival times. A door assignment heuristic is presented. The performance of the heuristic is compared with optimal solutions to small problems. The effectiveness of the proposed heuristic is studied under a variety of circumstances and terminal sizes. The simulation results show that the proposed heuristic is applicable to realistic-size terminals, and it is effective when variability in truck arrival and service times is considered.     

The determination of the optimal number of kanbans in a Just-In-Time production system

Just-In-Time (JIT) production is supported by the kanban inventory control and product scheduling system. It is important for production managers to determine the optimal number of kanbans in order to successfully operate a multi-line, multi-stage kanban production system. All relevant factors and costs must be considered before arriving at the optimal number of kanbans. In this paper, some JIT production factors such as demand, in process inventory, inventory and labor costs, subcontractor's supply capacity, and workload are discussed. And then, a model formulation using mixed integer goal programming is presented. Finally, a numerical example is presented in order to verify our model.     

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.     

The ARTEMIS under‐ice AUV docking system

The ARTEMIS docking system demonstrates autonomous docking capability applicable to robotic exploration of sub‐ice oceans and sub‐glacial lakes on planetary bodies, as well as here on Earth. In these applications, melted or drilled vertical access shafts restrict vehicle geometry as well as the in‐water infrastructure that may be deployed. The ability of the vehicle to return reliably and precisely to the access point is critical for data return, battery charging, and/or vehicle recovery. This paper presents the mechanical, sensor, and software components that make up the ARTEMIS docking system, as well as results from field deployment of the system to McMurdo Sound, Antarctica in the austral spring of 2015. The mechanical design of the system allows the vehicle to approach the dock from any direction and to pitch up after docking for recovery through a vertical access shaft. It uses only a small volume of in‐water equipment and may be deployed through a narrow vertical access shaft. The software of the system reduces position estimation error with a hierarchical combination of dead reckoning, acoustic aiding, and machine vision. The system provides critical operational robustness, enabling the vehicle to return autonomously and precisely to the access shaft and latch to the dock with no operator input.     

A rescheduling and cost allocation mechanism for delayed arrivals

We propose a solution to the problem of rescheduling a sequence of arrivals that are subject to a delay event at a common destination. Such situations include jobs arriving at a single production facility, aircraft whose landings are postponed, and ships that are inbound to a dock or lightering facility. Each arrival faces a nonlinear cost due to the delay, but the delay costs can be mitigated by allowing the arrivals to be reordered. We optimize the reordering process by designing a Vickrey–Clarke–Groves (VCG) mechanism to construct a payoff matrix describing the amounts necessary to move the currently assigned arrival slots either earlier or later. Using this payoff matrix, we compute the optimal reordering of the arrivals by utilizing the well-known solution to the assignment problem, which maximizes the benefit in a computationally efficient fashion. The VCG mechanism is strategyproof, that is, no arrival has an incentive to misreport the value of moving up or down in the sequence. We also show that participating in the centralized process is to no arrival׳s disadvantage. Because VCG procedures in general are subject to budget deficits, we provide alternative mechanisms to overcome this difficulty. Finally, we carry out computational experiments demonstrating that the VCG mechanism can be implemented for realistically-sized problem sets and that the cost savings are significant.     

一种新的自组装模块化群体机器人——对接机构设计与自组装控制

基于新型自组装模块化群体机器人Sambot,研究并实现了多个机器人之间的自主对接与自组装控制．首先, 提出了一种由对接卡扣与对接卡槽组成的新型对接机构,它可以使多个Sambot在一定对接偏差范围内,从前、后、 左、右4个方向同时进行对接;其次,采用基于行为的控制方法,仅依赖机器人自身红外传感器的局部感知和通信能力, 实现了对接机器人寻找目标、导航和自主对接等自组装行为;最后,成功完成了两个Sambot的自主对接与自组装控制实验． 实验结果表明,本文提出的自组装控制方法可以直接扩展到多个Sambot的情形,来构建任意构型的集合体机器人．     

Reliable pose estimation of underwater dock using single camera: a scene invariant approach

It is well known that docking of Autonomous Underwater Vehicle (AUV) provides scope to perform long duration deep-sea exploration. A large amount of literature is available on vision-based docking which exploit mechanical design, colored markers to estimate the pose of a docking station. In this work, we propose a method to estimate the relative pose of a circular-shaped docking station (arranged with LED lights on periphery) up to five degrees of freedom (5-DOF, neglecting roll effect). Generally, extraction of light markers from underwater images is based on fixed/adaptive choice of threshold, followed by mass moment-based computation of individual markers as well as center of the dock. Novelty of our work is the proposed highly effective scene invariant histogram-based adaptive thresholding scheme (HATS) which reliably extracts positions of light sources seen in active marker images. As the perspective projection of a circle features a family of ellipses, we then fit an appropriate ellipse for the markers and subsequently use the ellipse parameters to estimate the pose of a circular docking station with the help of a well-known method in Safaee-Rad et al. (IEEE Trans Robot Autom 8(5):624–640, 1992). We analyze the effectiveness of HATS as well as proposed approach through simulations and experimentation. We also compare performance of targeted curvature-based pose estimation with a non-iterative efficient perspective-n-point (EPnP) method. The paper ends with a few interesting remarks on vantages with ellipse fitting for markers and utility of proposed method in case of non-detection of all the light markers.     

Underwater docking of an under-actuated autonomous underwater vehicle: system design and control implementation

Underwater docking greatly facilitates and extends operation of an autonomous underwater vehicle (AUV) without the support of a surface vessel. Robust and accurate control is critically important for docking an AUV into a small underwater funnel-type dock station. In this paper, a docking system with an under-actuated AUV is presented, with special attention paid to control algorithm design and implementation. For an under-actuated AUV, the cross-track error can be controlled only via vehicle heading modulation, so both the cross-track error and heading error have to be constrained to achieve successful docking operations, while the control problem can be even more complicated in practical scenarios with the presence of unknown ocean currents. To cope with the above issues, a control scheme of a three-hierarchy structure of control loops is developed, which has been embedded with online current estimator/compensator and effective control parameter tuning. The current estimator can evaluate both horizontal and vertical current velocity components, based only on the measurement of AUV’s velocity relative to the ground; in contrast, most existing methods use the measurements of both AUV’s velocities respectively relative to the ground and the water column. In addition to numerical simulation, the proposed docking scheme is fully implemented in a prototype AUV using MOOS-IvP architecture. Simulation results show that the current estimator/compensator works well even in the presence of lateral current disturbance. Finally, a series of sea trials are conducted to validate the current estimator/compensator and the whole docking system. The sea trial results show that our control methods can drive the AUV into the dock station effectively and robustly.     

tPSODock:基于化学得分函数和两层粒子群算法的计算机分子对接程序

药物分子对接是计算机辅助药物设计的主要方法之一。利用化学得分函数(Chemscor)作为能量函数,以及将一种新的优化算法一两层粒子群算法作为搜索算法,得到了一种新的计算机分子对接程序：tPSODock。利用tPSODock计算了100个蛋白质一配体的复合物,并且与Consdock和Autodock3．0计算结果进行了对比,结果显示88％的计算结果RMSD小于2．0A,优于Consdock以及Autodock的计算结果。说明tPSODock在是一种高效的分子对接软件,可以用于大规模数据库的筛选工作,适合新药的开发和研制。     

Trajectory generation for the N-trailer problem using Goursatnormal form

Develops the machinery of exterior differential forms, more particularly the Goursat normal form for a Pfaffian system, for solving nonholonomic motion planning problems, i.e., motion planning for systems with nonintegrable velocity constraints. The authors use this technique to solve the problem of steering a mobile robot with n trailers. The authors present an algorithm for finding a family of transformations which will convert the system of rolling constraints on the wheels of the robot with n trailers into the Goursat canonical form. Two of these transformations are studied in detail. The Goursat normal form for exterior differential systems is dual to the so-called chained-form for vector fields that has been studied previously. Consequently, the authors are able to give the state feedback law and change of coordinates to convert the N-trailer system into chained-form. Three methods for planning trajectories for chained-form systems using sinusoids, piecewise constants, and polynomials as inputs are presented. The motion planning strategy is therefore to first convert the N-trailer system into Goursat form, use this to find the chained-form coordinates, plan a path for the corresponding chained-form system, and then transform the resulting trajectory back into the original coordinates. Simulations and frames of movie animations of the N-trailer system for parallel parking and backing into a loading dock using this strategy are included