An exact algorithm for a cross-docking supply chain network design problem

This paper proposes a branch-and-price algorithm as an exact algorithm for the cross-docking supply chain network design problem introduced by one of the authors of this paper. The objective is to optimally locate cross-docking (CD) centres and allocate vehicles for direct transportation services from the associated origin node to the associated CD centre or from the associated CD centre to the associated destination node so as to satisfy a given set of freight demands at minimum cost subject to the associated service (delivery) time restriction. A set-partitioning-based formulation is derived for the problem for which some solution properties are characterized. Based on the properties, a branch-and-price algorithm is derived. The properties can also be used in deriving any efficient local search heuristics with the move operation (neighbourhood search operation) of modifying assignment of some freight demands from current CD centres to other CD centres. Computational experiments show that the branch-and-price algorithm is effective and efficient and also that the solution properties contribute to improve the efficiency of the local search heuristics.     

带批次和临时库存的越库配送车辆路径问题研究

从零售业供应链整合入手,构建供应商、配送中心和零售点构成的协同配送网络,研究带批次和临时库存的越库配送车辆路径问题.将越库过程分为取货、分拣和配货三个阶段,考虑配送中心分拣能力,分批次设置车辆协同到达配送中心的服务时刻,据此建立以最小化车辆运输成本、临时库存成本和固定成本为目标的数学模型.考虑问题特征,设计一种混合变邻域搜索粒子群算法求解,并将结果进行横纵向比较.结果表明,所提算法有效且可靠,能够为带批次和临时库存的越库配送问题提供解决方案.     

Adaptive multi-restart Tabu Search algorithm for the vehicle routing problem with cross-docking

This paper deals with a multi-source vehicle routing problem with a cross-docking facility, and studies open and closed network configurations as well as practically relevant dependency rules and consolidation decisions. Given a set of supplier–customer pairs with known demands, the aim is to design minimum cost routes for the transportation of products via a cross-dock. Vehicles cannot travel directly from suppliers to customers, and thus, products arriving from inbound vehicles are sorted and consolidated onto outbound vehicles. The proposed method utilizes an adaptive multi-restart local search framework. For this purpose, a Tabu Search algorithm is employed, while the execution of the re-starting mechanism is based on the information extracted from a reference set of solutions. Computational experiments illustrate the efficiency and effectiveness of the proposed method. Compared to existing results, new improved upper bounds are reported.     

Storage yard operations in container terminals: Literature overview,trends, and research directions

Inbound and outbound containers are temporarily stored in the storage yard at container terminals. A combination of container demand increase and storage yard capacity scarcity create complex operational challenges for storage yard managers. This paper presents an in-depth overview of storage yard operations, including the material handling equipment used, and highlights current industry trends and developments. A classification scheme for storage yard operations is proposed and used to classify scientific journal papers published between 2004 and 2012. The paper also discusses and challenges the current operational paradigms on storage yard operations. Lastly, the paper identifies new avenues for academic research based on current trends and developments in the container terminal industry.     

Minimizing the makespan in a two-machine cross-docking flow shop problem

This paper studies a two-machine cross-docking flow shop scheduling problem in which a job at the second machine can be processed only after the processing of some jobs at the first machine has been completed. The objective is to minimize the makespan. We first show that the problem is strongly NP-hard. Some polynomially solvable special cases are provided. We then develop a polynomial approximation algorithm with an error-bound analysis. A branch-and-bound algorithm is also constructed. Computational results show that the branch-and-bound algorithm can optimally solve problems with up to 60 jobs within a reasonable amount of time.     

Synchronization analysis of a complex network family

This paper is concerned with a meaningful and challenging problem: Is it possible to establish synchronization criteria for a network family, the members of which have different network structure? Based on the parameter-dependent Lyapunov function, some synchronization criteria are proposed to address this problem. These simple yet generic criteria can lead to the advantage of easy synchronization verification of every member from the network family. On the other hand, the problem mentioned above can be regarded as a synchronization problem for a network with structure uncertainty, which is also investigated in this paper. Numerical examples are given to demonstrate the effectiveness of the derived criteria.     

Better management of blood supply-chain with GIS-based analytics

This paper presents a novel application of operations research, data mining and geographic information-systems-based analytics to support decision making in blood supply chain management. This, blood reserve availability assessment, tracking, and management system (BRAMS), research project has been funded by the Office of the Secretary of Defense. (This DoD funded SBIR project is performed by the researchers at Knowledge Based Systems, Inc. (KBSI).) The rapidly increasing demand, criticality of the product, strict storage and handling requirements, and the vastness of the theater of operations, make blood supply-chain management a complex, yet vital problem for the department of defense. In order to address this problem a variety of contemporary analytic techniques are used to analyze inventory and consumption patterns, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The current implementation of the system is being actively used by 130 mangers at different levels in the supply chain including facilities at Osan Air Force Base in South Korea and Incirlik Air Force Base in Turkey.     

Improved MILP models for two-machine flowshop with batch processing machines

In this paper, we consider the problem of scheduling jobs in a flowshop with two batch processing machines such that the makespan is minimized. Batch processing machines are frequently encountered in many industrial environments such as heat treatment operations in a steel foundry and chemical processes performed in tanks or kilns. Improved Mixed Integer Linear Programming (MILP) models are presented for the flowshop problem with unlimited or zero intermediate storage. An MILP-based heuristic is also developed for the problem. Computational experiments show that the new MILP models can significantly improve the original ones. Also, the heuristic can obtain the optimal solutions for all the test problem instances.     

Chaos synchronization for master slave piecewise linear systems: Application to Chua’s circuit

This paper deals with chaos synchronization for master slave piecewise linear systems. The synchronization problem is formulated as a global stability problem of error synchronization dynamics. New sufficient conditions are provided using a Lyapunov approach and the so-called S-procedure. We show that the synchronization problem can be solved as an optimization problem subject to a set of Linear Matrix Inequalities (LMI) for which a state feedback controller is designed efficiently. The effectiveness of the proposed solution is verified via simulation results using the original Chua’s circuit model. Furthermore, it will be proven that the new sufficient conditions relaxed the conservatism of previous existing works.     

The vehicle routing and scheduling problem with cross-docking for perishable products under uncertainty: Two robust bi-objective models

This paper presents a bi-objective MILP model for the vehicle routing and scheduling problem with cross-docking for perishable products. It is demonstrated that considering merely one objective sacrifices the other one and that the L₁ metric method makes a suitable trade-off. Two robust models are developed when the travel time of the outbound vehicles and the freshness-life of the products are uncertain. The results show that the effect of the appearing uncertainty in the travel time on the deterioration of the objectives is higher than the effect of the freshness-life of the products, and using the proposed model, the freshness of the delivered products increases by 74.14% on average without increasing the distribution cost, which can decrease the waste.     

Pinning adaptive synchronization of a class of uncertain complex dynamical networks with multi-link against network deterioration

For the reason that the uncertain complex dynamic network with multi-link is quite close to various practical networks, there is superiority in the fields of research and application. In this paper, we focus upon pinning adaptive synchronization for uncertain complex dynamic networks with multi-link against network deterioration. The pinning approach can be applied to adapt uncertain coupling factors of deteriorated networks which can compensate effects of uncertainty. Several new synchronization criterions for networks with multi-link are derived, which ensure the synchronized states to be local or global stable with uncertainty and deterioration. Results of simulation are shown to demonstrate the feasibility and usefulness of our method.     

A travel time estimation model for a high-level picker-to-part system with class-based storage policies

Most previous related studies on warehouse configurations and operations only investigated single-level storage rack systems where the height of storage racks and the vertical movement of the picking operations are both not considered. However, in order to utilize the space efficiently, high-level storage systems are often used in warehouses in practice. This paper presents a travel time estimation model for a high-level picker-to-part system with the considerations of class-based storage policy and various routing policies. The results indicate that the proposed model appears to be sufficiently accurate for practical purposes. Furthermore, the effects of storage and routing policies on the travel time and the optimal warehouse layout are discussed in the paper.     

Adaptive synchronization of Cohen-Grossberg neural networks with unknown parameters and mixed time-varying delays

In this paper, we investigate the synchronization problem of chaotic Cohen-Grossberg neural networks with unknown parameters and mixed time-varying delays. An adaptive linear feedback controller is designed to guarantee that the response system can be synchronized with a drive system by utilizing Lyapunov stability theory and parameter identification. Our synchronization criteria are easily verified and do not need to solve any linear matrix inequality. These results generalize a few previous known results and remove some restrictions on amplification function and time delay. This research also demonstrates the effectiveness of application in secure communication. Numerical simulations are carried out to illustrate the main results.     

Scheduling the truckload operations in automatic warehouses

This work presents a scheduling problem that arises in an automatic storage/retrieval warehouse system AS/RS involving the scheduling of the truck load operations. The truck loading operations are modelled as job shop problem with recirculation. The loads are considered as jobs, the pallets of a load are seen as the job’s operations. The forklifts are the machines. The minimization of the makespan allows minimizing the idle time of the warehouse’s equipments.     

Defining order picking policy: A storage assignment model and a simulated annealing solution in AS/RS systems

Improving technology, variable customer demands, variety of products and increasing improvement of production systems has brought storage facilities, which has an important role on business operations, to a critical point. This circumstance has revealed the necessity on activating of storage systems and operations. In this study, mathematical model, which minimizes simultaneously storage allocation, storage retrieval and storage keeping costs, is generated for an AS/RS system of an enterprise. The mathematical model has run for small solution space and optimal solution is obtained. The problem in this study is an NP hard problem that is why optimal solution cannot be obtained for large solution spaces. So the problem in existing system is solved by using simulated annealing and an optimal order policy is proposed.     

Local adjustments: A general algorithm

Processing a set of operations on a single processor that can handle at most one job at a time is an underlying issue of many combinatorial optimization problems, and especially classical scheduling problems, such as job-shops, flow-shops and other X-shops. The main goal of local operations is to narrow the time-windows of operations for that kind of disjunctive scheduling problem.In this paper, we investigate the properties of local adjustments and provide a unified and efficient framework for the combination of the main adjustment procedures. Beyond its rapid prototyping feature, our implementation is proved to guarantee a good stability property that finally leads to a better convergence process. Computational experiments on single machine and on job-shop scheduling problems are reported.     

Service network design with management and coordination of multiple fleets

We present a new optimization model for the tactical design of scheduled service networks for transportation systems where several entities provide service and internal exchanges and coordination with neighboring systems is critical. Internal exchanges represent border crossings necessitating changes of vehicles, while the coordination with neighboring systems represents intermodal operations. For a given demand, the model determines departure times of the services such that throughput time of the demand in the system is minimized. The model is an extension of the design-balanced capacitated multicommodity network design model that we denote service network design with asset management and multiple fleet coordination to emphasize the explicit modeling of different vehicle fleets. Data from a real-world problem addressing the planning of new rail freight services across borders serves to illustrate the capabilities of the formulation. We analyze how synchronization with collaborating services and removal of border-crossing operations impact the throughput time for the freight. We identify a significant potential for system performance enhancement from synchronization among collaborating services for the problem studied.     

Local search algorithms for the multiprocessor flow shop scheduling problem

The multiprocessor flow shop scheduling problem is a generalization of the ordinary flow shop scheduling problem. The problem consists of both assigning operations to machines and scheduling the operations assigned to the same machine. We review the literature on local search methods for flow shop and job shop scheduling and adapt them to the multiprocessor flow shop scheduling problem. Other local search approaches we consider are variable-depth search and simulated annealing. We show that tabu search and variable-depth search with a neighborhood originated by Nowicki and Smutnicki outperform the other algorithms.     

A Hybrid Genetic Algorithm for Assembly Line Balancing

This paper presents a hybrid genetic algorithm for the simple assembly line problem, SALBP-1. The chromosome representation of the problem is based on random keys. The assignment of the operations to the workstations is based on a heuristic priority rule in which the priorities of the operations are defined by the chromosomes. A local search is used to improve the solution. The approach is tested on a set of problems taken from the literature and compared with other approaches. The computation results validate the effectiveness of the algorithm.     

Modelling and Optimal Receding-horizon Control of Maritime Container Terminals

The main objective of this paper consists in modelling, optimizing, and controlling container transfer operations inside intermodal terminals. More specifically, maritime container terminals are here considered, involving three kinds of transportation modes, i.e., maritime, rail, and road transport. Generally speaking, an intermodal port terminal can be seen as a system of container flows with two interfaces, towards the hinterland and towards the sea, respectively. Moreover, inside a terminal, unloading operations of inbound containers, container storage, and loading operations of outbound containers are carried out. A simple model for maritime container terminals is proposed in this paper. In the model, a system of queues represents the standing of containers and their movements inside the terminal. The dynamic evolutions of these queues are described by discrete-time equations, where the state variables represent the queue lengths and the control variables take into account the utilization of terminal resources such as load/unload handling rates. On the basis of the proposed model, an optimization problem is defined that consists in minimizing the transfer delays of containers in the terminal. The problem is stated as an optimal control problem whose solution is sought by adopting a receding-horizon strategy.