Joint planning for yard storage space and home berths in container terminals

Yard planning is essential for efficient operations in container terminals, especially for ports with limited storage space. To improve the utilisation of space and the efficiency of container handling in a terminal, operators require flexible yard space planning strategies to manage job workloads and yard-to-berth transportation costs. In previous studies, the inter-related decision making process for berths and yards has normally been studied separately, and yard planning models are designed with deterministic inputs of berths, where many existing terminals are operating with sub-optimal efficiency. In this paper, we consider different policies of the scattered stacking strategy for export containers and analyse the entire cycle of container handling from yard block to home berth, where the home berth is a quay section which includes the preferred berthing place of a vessel upon its arrival. We analyse three stacking policies, namely exclusive, cross-area, and buffer-area stacking policies, and formulate the planning problem for yard storage and related home berths into MILP (mixed integer linear programming) models. Solutions are obtained with a two-stage approach method. The numerical analysis demonstrates that the workload imbalance can be significantly reduced by implementing either the cross-area or buffer-area container stacking policy.     

Optimised loading patterns for intermodal trains

This paper considers one important aspect of operations planning referred to hereafter as train planning. Train planning is the process of spatially assigning containers to specific wagons (also known as railcars) on an intermodal train. The spatial arrangement of containers on a train can have a significant influence over the amount of time and energy consumed in the handling of containers. Efficient train planning can also maximise utilisation of wagon carrying capacity. This study proposes a mixed-integer programming model to determine the arrangement of containers on a train to minimise a weighted sum of number of wagons required and equipment working time. Due to the large number of variables, the proposed model cannot be solved in a timely manner for practical problems. This is addressed by applying heuristic algorithms local search and simulated annealing. Discrete-event simulation of an intermodal terminal is used to evaluate the proposed methods and to illuminate various properties of the model.     

Data envelopment analysis of AGV fleet sizing at a port container terminal

A decision-making approach based on Data Envelopment Analysis (DEA) for determining the efficient container handling processes (considering the number of employed Automated Guided Vehicles (AGVs)) at a port container terminal (PCT) is presented in this paper. Containers are unloaded from the ship by quay cranes and transported to the storage area by AGVs. We defined performance measures of proposed container handling processes and analysed the effects when changing the number of AGVs. The values of performance measures were collected and/or calculated from simulation. Container handling process, with a fixed number of quay cranes, when a different number of AGVs is used to transport containers from berth to assigned locations within storage area, represents a decision-making unit (DMU). We applied the basic CCR (Charnes, Cooper and Rhodes) DEA model with two inputs: average ship operating delay costs and average operating costs of employed equipment at a PCT, and two outputs: average number of handled import containers per ship and weighted average utilisation rate of equipment at a PCT. DEA method proved to be useful when testing different DMUs and when determining efficient DMUs for planning purposes. This study shows that efficiency evaluation of AGV fleet sizing and operations is useful for planning purposes at PCTs.     

Physical Internet,conventional and hybrid logistic systems: a routing optimisation-based comparison using the Eastern Canada road network case study

The Physical Internet (PI) logistics system is an innovative logistics concept that has been gathering a lot of attention lately. This system consists of open, modular and shared containers and transit hubs to move goods globally. The purpose of this paper is to compare the performance of PI with regard to the conventional (CO) logistics system in order to quantify the advantages and disadvantages of PI from a truck and driver routing perspective with an explicit constraint on maximum return time for drivers. The comparison presented in this work is carried out through Monte-Carlo simulation within a sequential three-phase optimisation framework. Based on our analysis, PI reduces driving distance (and time), GHG (greenhouse gas) emissions and the social cost of truck driving. On the other hand, it increases the number of container transfers within the PI logistics centres. This insight is a contribution of the paper and reinforces the current literature on PI. The other main contribution of the paper is a validation of the claim that the number of drivers who can go back home at the end of a work day remains consistently high in PI, regardless of the traffic level.     

Environment conscious manufacturing edited by S.M. Gupta and A.J.D. Lambert

The dynamic facility layout problem (DFLP) aims to minimise the sum of handling and re-layout costs by devising an individual layout for each distinctive production period. In this paper, a hybrid particle swarm optimisation (HPSO) algorithm is proposed to find near-optimal solutions of DFLP. We use a coding and decoding technique that permits a one to one mapping of a solution in discrete space of DFLP to a PSO particle position in continuous space. The proposed PSO will further use this coding technique to explore the continuous solution space. For further enhancement, the proposed PSO is hybridised with a simple and fast simulated annealing. The developed algorithm is capable of being extended to more general cases although equal area machines and standardised handling equipments with identical unit costs are assumed for the time being. Computational results show the efficiency of the proposed algorithm compared to other heuristics.     

Determination of the number of containers,production kanbans and withdrawal kanbans; and scheduling in kanban flowshops - Part 1

In the first part of this paper, we consider a kanban-controlled flowshop and present recursive equations for time-tabling of containers in a given sequence. The flowshop is characterized by the following: a production batch of a part-type (or job) divided into kanban lots or containers; production kanbans to control the loading of containers on machines or workstations; withdrawal kanbans to regulate the movement of containers between two consecutive buffer storages; periodic material handling of containers; dual blocking mechanisms operative on workstations and material handling; and sequence-dependent set-up times of containers. Considering different types of problems, recursive equations have been developed for time-tabling of containers in a given sequence.     

车辆战术储备器材包装单元装载优化研究

目的通过对车辆战术储备器材包装单元化装载问题展开研究,为提高部队车辆战术储备器材包装单元装载能力提供技术与方法依据。方法分析装载优化模型的空间、质量、装载平衡和摆放稳定性等主要约束以及约束的处理方法,运用启发式算法对模型求解流程进行合理设计,并提出启发式算法和遗传算法相结合的混合遗传算法,以托盘装载为例说明具体装载过程。结果算例结果表明,托盘空间利用率达到了98.3%以上,装载单元集装稳定性高。结论该算法可减少装载容器数量,提升容器装载能力,优化器材包装单元装载,对提高车辆战术储备器材快速保障能力具有重要意义。     

Determination of the number of containers,production kanbans and withdrawal kanbans; and scheduling in kanban flowshops - Part 2

We consider the problem of determination of the number of containers or container size, production kanbans and withdrawal kanbans, and scheduling of containers in presence of material handling between workstations, and dual blocking mechanisms operative on both workstations and material handling. A heuristic is proposed to address the problem of determining the number of containers, and production and withdrawal kanbans, and also determining the sequence of containers to minimize the sum of weighted flowtime, weighted earliness and weighted tardiness of containers. Recursive equations, developed in part 1 of this paper, are used for time-tabling of the sequence of containers. An extensive performance evaluation of the heuristic and a benchmark procedure, based on random search, has been carried out by generating a number of problems of various sizes.     

Container sequencing for quay cranes with internal reshuffles

Fast handling of vessels is one of the most important goals in container terminal operations planning. In recent studies, quay crane double cycling has been investigated to accelerate the service of vessels. In our paper, we show that the service process can be further accelerated by changing the treatment of so-called reshuffle containers. Reshuffle containers have to be removed from their position in the vessel only to gain access to containers stacked below them. Our approach enables to reposition reshuffle containers directly within the bay of a vessel, referred to as internal reshuffles, instead of temporarily unloading them. A mathematical problem formulation and a heuristic solution method, namely a greedy randomized adaptive search procedure, are provided for planning crane operations under internal reshuffles. Computational tests prove that the consideration of internal reshuffles leads to a further shortening of vessel handling times compared to a sole application of crane double cycling.     

An effective heuristic for scheduling a yard crane to handle jobs with different ready times

In land-constrained port container terminals, yard cranes are commonly used for handling containers in a container yard to load containers onto or unload containers from trucks. However, yard cranes are bulky, slow and need to move frequently between their work locations. As it is common that the container flow in a terminal is bottlenecked by yard crane operations, effective work schedules of yard cranes are needed to increase the terminal’s throughput. This article studies the problem of scheduling a yard crane to perform a given set of container handling jobs with different ready times. The objective is to minimize the sum of job waiting times. It is noted that the scheduling problem is NP-complete. This research develops a heuristic to solve the scheduling problem and an algorithm to find lower bounds for benchmarking the schedules found by the heuristic. The performance of the heuristic is evaluated by a set of test problems generated on the basis of real-life terminal operations data. Indeed, the computational results show that the proposed heuristic can find effective solutions for the scheduling problem.     

Analysis on container port capacity: a Markovian modeling approach

Container ports handle outbound, inbound, and transshipment containers plying between the area for vessels on the quay and the storage space in the yard. Port operators typically concentrate their efforts on the container handling process with the aims of increasing the productivity of quay-side operations and reducing the time in port of vessels. Recognizing that operation processes necessitate containers to stay in the storage space for a certain period before moving to other areas, the operational efficiency at the yard (in addition to that at the quayside) plays an influential role in ensuring performance measures of a container port. This study develops analytical models based on the Markov chain to estimate the port capacity under various combinations of resources, namely, quay cranes, yard cranes, and prime movers. Important performance measures representing the capacity in the proposed models are analyzed and sensitivity analyses of the port capacity are conducted through numerical experiments. The results under the suggested operational strategies are also compared.     

Lean-pull strategy in a re-entrant manufacturing environment: a pilot study for TFT-LCD array manufacturing

The increase of a panel's size in thin film transistor – liquid crystal display (TFT-LCD), results in an increase in stock space and increased cost from work-in-process (WIP). This paper proposes a lean-pull strategy, combining buffers with CONWIP (CONstant work-in-process), which results in shared resources to a re-entrant process in TFT-LCD manufacturing. The buffer size and CONWIP levels are the decision variables and are solved by simulation optimisation. The proposed procedure is applied to a factory that manufactures TFT-LCD. The study shows that the proposed lean-pull strategy can reduce the cycle time and achieve a reduction of 34.57% in WIP. The automated material handling systems (AMHS) stocker utilisation can be reduced from 62.13% to 18.49% without additional investment or facilities. Sensitivity analysis indicates the maximum daily throughput will achieve over 10% improvement. The empirical results from this pilot study provide useful managerial insights for the production control of array manufacturing.     

Integrated nuclear data utilisation system for innovative reactors

A five-year research and development project on an integrated nuclear data utilisation system was initiated in 2002, for developing innovative nuclear energy systems such as accelerator-driven systems. The integrated nuclear data utilisation system will be constructed as a modular code system, which consists of two sub-systems: the nuclear data search and plotting sub-system, and the nuclear data processing and utilisation sub-system. The system will be operated with a graphical user interface in order to enable easy utilisation through the Internet by both nuclear design engineers and nuclear data evaluators. This paper presents an overview of the integrated nuclear data utilisation system, describes the development of a prototype system to examine the operability of the user interface and discusses specifications of the two sub-systems.     

Development of a simulation-based optimisation for controlling operation allocation and material handling equipment selection in FMS

Flexible manufacturing system (FMS) is described as a set of computerised numerical controlled machines, input–output buffers interconnected by automated material handling devices. This paper develops a bi-objective operation allocation and material handling equipment selection problem in FMS with the aim of minimising the machine operation, material handling and machine setup costs and maximising the machine utilisation. The proposed model is solved by a modified chaotic ant swarm simulation based optimisation (CAS²O) while applying pre-selection and discrete recombination operators is surveyed a capable method to simulate different experiments of FMS problems. A test problem is selected from the literature to evaluate the performance of the proposed approach. The results validate the effectiveness of the proposed method to solve the FMS scheduling problem.     

ELEMENTS OF WAREHOUSE LAYOUT

The work summarised in this paper has been directed to examine the basic requirements of warehouse layouts. Two simple types of layout have been examined and equations derived for the dimensioning of these, given such information as total volume of stock and number of stock lines. A sketch of the layouts is given.

Ten factors have been considered in arriving at the theoretical layouts and it is shown that different types of layout are affected by different factors, some layouts being independent of factors to which others are sensitive.

Dimensions of a layout can be calculated to minimise handling distance, handling time or space utilisation. Where cost functions are available for these parameters, total cost can also be minimised. The formulae lend themselves readily to computer manipulation, enabling an optimum layout to be determined given only the number of stock lines and volumes stored.     

An artificial bee colony algorithm for the economic lot scheduling problem

In this study, we present an artificial bee colony (ABC) algorithm for the economic lot scheduling problem modelled through the extended basic period (EBP) approach. We allow both power-of-two (PoT) and non-power-of-two multipliers in the solution representation. We develop mutation strategies to generate neighbouring food sources for the ABC algorithm and these strategies are also used to develop two different variable neighbourhood search algorithms to further enhance the solution quality. Our algorithm maintains both feasible and infeasible solutions in the population through the use of some sophisticated constraint handling methods. Experimental results show that the proposed algorithm succeeds to find the all the best-known EBP solutions for the high utilisation 10-item benchmark problems and improves the best known solutions for two of the six low utilisation 10-item benchmark problems. In addition, we develop a new problem instance with 50 items and run it at different utilisation levels ranging from 50 to 99% to see the effectiveness of the proposed algorithm on large instances. We show that the proposed ABC algorithm with mixed solution representation outperforms the ABC that is restricted only to PoT multipliers at almost all utilisation levels of the large instance.     

Positioning empty containers among multiple ports with leasing and purchasing considerations

With the recent development of container transportation, the imbalance of empty containers among ports has become more serious. We consider the problem of positioning empty containers. The goal of this study is to propose a plan for transporting empty containers between container ports (terminals) to reduce the imbalance. There is currently a demand at each port and any backlog of containers is not permitted. The objective is to minimize the total relevant costs such as transportation cost, handling cost, and holding cost, etc. In this study, we develop a model with respect to the leasing and purchasing of containers. Mixed integer programming and genetic algorithms are used to solve the model. A hybrid GA is also proposed to reduce the computation time while still obtaining an acceptable result.     

Comparison of reusable and single‐use plastic and paper shipping containers for distribution of fresh pineapples

This paper presents the effects of different packaging systems and fruit orientation on bruising and pre‐cooling time of pineapples during distribution. The package types studied were reusable plastic containers, single‐use paper corrugated containers and plastic foam containers (FCs). Simulated vibration tests were performed to evaluate the shipping containers on their protective performances. After the vibration tests, pineapples were evaluated for bruise damage and decay during storage for 5 days. Pineapple fleshes were also evaluated for bruise volume and changes in colour, firmness, total soluble solids content (TSS) and titratable acidity (TA) after storage of 5 days. Bruise damage was more intense as the storage time increased. Package types had significant effects (p ≤ 0.05) on bruise damage of pineapples. The corrugated containers showed the best protective performance for pineapples, while the FCs showed the worst. The corrugated containers with paperboard partitions showed the lowest damage levels as compared to other package types studied. Foam‐net cushion reduced bruise damage of pineapples. L values and firmness of pineapple flesh were highly associated with degree of bruising. The results suggested that slight bruising on the skin may signify severe bruising on the flesh and bruising accelerated decay in pineapples. Orientation did not show a significant effect (p ≤ 0.05) on bruising. The highest pre‐cooling rates were observed in the reusable plastic containers, while the slowest rates were observed in the single‐use paper containers. The results indicated that careful handling in the proper packaging with optimum cushion can minimize bruise damage and decay of pineapples after shipments. Copyright © 2007 John Wiley & Sons, Ltd.     

Flexible space-sharing strategy for storage yard management in a transshipment hub port

In this paper, a storage yard planning problem is studied for a transshipment port with limited space and high-throughput level. Generally, the consignment strategy is used in the yard for a transshipment port, where containers to the same destination vessel are stored together. This is to facilitate faster loading process as it reduces reshuffles as well as long distance movements of yard cranes. However, the consignment strategy is known to be inefficient in space utilization since each storage location must be dedicated to a particular vessel. To improve the space utilization while retaining the advantage of consignment, a new approach named the “flexible space-sharing strategy” is proposed. The idea is that the container space can be shared by two different vessels as long as their containers do not occupy the space at the same time. This strategy allows the same storage location to be reserved for two vessels. The amount of space will only be allocated to a specific vessel on the arrival of corresponding containers. By controlling where to stack the containers in the storage locations, the containers to each vessel are not mixed and the consignment feature can be preserved. This strategy is first formulated as a mixed integer program (MIP). As the MIP model has a block diagonal structure, we develop a search algorithm which combines MIP and heuristics to find the solution. The numerical experiments show that the “flexible space-sharing strategy” can handle much more containers within the same storage space compared with the “non-sharing strategy”.