With advancements of quay side equipments and technologies, the bottleneck of port operations has moved from quay side to yard side. The yard management of a port has significant influences on the competitiveness of a port in the global shipping network. The research area of yard management has attracted a lot of attentions from both the academia and the industrial practitioners. This paper gives a comprehensive review for the studies on the yard management in container terminals. From three aspects, i.e., yard cranes management, yard vehicles management, and yard spaces management, this paper reports the advances in these three areas. Some future directions on the yard management researches are also discussed. The purpose of this paper is to stimulate more practically relevant researches in this emerging area.

The semiconductor industry has grown rapidly, and subsequently production planning problems have raised many important research issues. The reentrant flow-shop (RFS) scheduling problem with time windows constraint for harddisk devices (HDD) manufacturing is one such problem of the expanded semiconductor industry. The RFS scheduling problem with the objective of minimizing the makespan of jobs is considered. Meeting this objective is directly related to maximizing the system throughput which is the most important of HDD industry requirements. Moreover, most manufacturing systems have to handle the quality of semiconductor material. The time windows constraint in the manufacturing system must then be considered. In this paper, we propose a hybrid genetic algorithm (HGA) for improving chromosomes/offspring by checking and repairing time window constraint and improving offspring by left-shift routines as a local search algorithm to solve effectively the RFS scheduling problem with time windows constraint. Numerical experiments on several problems show that the proposed HGA approach has higher search capability to improve quality of solutions.

In recent years, for the purpose of solving the problem regarding environment protection and resource saving, certain measures and policies have been promoted to establish a green supply chains (GSC) with material flows from collection of used products to reuse of recycled parts in production of products. In this study, we propose an optimal operation of the GSC while considering the collection incentive of the used products and quality for recycling of used products. Two types of decision-making approaches are used for product quantity, collection incentive of used products and lower limit of quality level of reusable parts in the used products for recycling in the GSC. One is the decision-making under an independent policy in decentralized supply chains where a retailer and a manufacturer make decisions so as to maximize profits individually. The other is the decision-making under a cooperative policy in centralized supply chains where a retailer and a manufacturer make decisions cooperatively so as to maximize the whole system's profit. Additionally, we also discuss supply chain coordination as a manufacturer-retailer partnership based on profit sharing. Furthermore, we show the effect of the quality of the reusable parts on the optimal decisions. The collection incentive of the used products was found to bring more profitability to the GSC activity.

A surface mount device (SMD) assembles electronic components on printed circuit boards (PCB). Since a component assembly process is a bottleneck process in a PCB assembly line, making an efficient SMD plan is critical in increasing the PCB assembly line productivity. Feeder assignment is an important part of the SMD plan optimization. In this paper, we propose a feeder re-assign improvement algorithm for a specific type of SMD machine with a piano type multi-head gantry. Computational results on some real-world benchmark data sets show the effectiveness of our proposed algorithm.

This paper proposes a mathematical modeling-based approach for assessing disaster effects and selecting suitable mitigation alternatives to provide humanitarian relief (HR) supplies, shelter, rescue services, and long-term services after a disaster event. Mitigation steps, such as arrangement of shelter and providing HR items (food, water, medicine, etc.) are the immediate requirements after a disaster. Since governments and non-governmental organizations (NGOs) providing humanitarian aid need to know the requirements of relief supplies and resources for collecting relief supplies, organizing and initiating mitigation steps, a quick assessment of the requirements is the precondition for effective disaster management. Based on satellite images from weather forecasting channels, an area/dimension of the disaster-affected zones and the extent of the overall damage may often be obtained. The proposed approach then estimates the requirements for HR supplies, supporting resources, and rescue services using the census and other government data. It then determines reliable transportation routes, optimum collection and distribution centers, alternatives for resource support, rescue services, and long-term help needed for the disaster-affected zones. A numerical example illustrates the applicability of the model in disaster mitigation planning.

This paper proposes a multiobjective model describing the trade-offs involved in selecting the locations of drop-off boxes for collecting used products and transporting these products to designated locations. We assume the following reverse flow of used products. Owners of used products (cellular phones, digital cameras, ink cartridges, etc.) take them to the nearest drop-off box when the distance is reasonably short. We also assume that owners living closer to drop-off boxes dispose of more used products than do owners living farther from drop-off boxes. Different types of used products are collected, with each type requiring its own drop-off box. A transportation destination for each product is specified. Three objectives are considered: maximizing the volume of used products collected at drop-off boxes; minimizing the cost of transporting collected products to designated locations; and minimizing the cost of allocating space for drop-off boxes. We formulate the above model as a multiobjective integer programming problem and generate the corresponding set of Pareto optimal solutions. We apply the model to an area using population data for Chofu City, Tokyo, Japan, and analyze the trade-offs between the objectives.

The amount of international trade is rapidly increasing as a result of globalization. It is well known that as the size of a vessel becomes larger, the transportation cost per container decreases. That is, the economy-of-scale holds even in maritime container transportation. As a result, the sizes of containerships have been steadily increased for reducing transportation costs. In addition, various handling technologies and handling equipment have been introduced to increase the throughput capacities of container terminals. Quay crane (QC) that carries out load/unload operations plays the most important role among various handling equipment in terminals. Two typical examples of advanced QC concepts proposed so far are double trolley QC and supertainer QC. This paper suggests a method of estimating the expected value and the standard deviation of the container handling cycle time of the advanced QCs that involve several handling components which move at the same time. Numerical results obtained by the proposed estimation procedure are compared with those obtained by simulation studies. In order to demonstrate the advantage of advanced QCs, we compared their expected cycle times with those of a conventional QC.

Efficiency in work training is a perennial issue due to high-diversity low-volume production, particularly for manufacturers producing office machines which are manually assembled by workers. To reduce the training cost, parts used in training are usually reused; a trainer disassembles a product assembled by a worker in training. This paper proposes a training method that employs disassembly usually performed by a trainer. This method assigns both assembly and disassembly to a worker in training, in contrast to the conventional method. The effectiveness of the proposed method is experimentally discussed in terms of learning assembly motions and work procedure at each learning stage, namely, "undergoing learning," "immediately after learning," and "seven days after learning." The effectiveness of the training method is confirmed. The method improves the stability of work procedure recollection immediately after training. Furthermore, at seven days after training, it improves retention of the assembly motions and work procedure, and also promotes and maintains memory related to product structure.

Large variation in electrocardiogram (ECG) waveforms continues to present challenges in defining R-wave locations in ECG signals. This research presents a procedure to extract the R-wave locations by forward-backward (FB) algorithm and classify the arrhythmic beat conditions by using RR intervals. The FB algorithm shows forward and backward searching rules from QRS onset and eliminates lower-amplitude signals near the baseline using a statistical process control concept. The proposed algorithm was trained the optimal parameters by using MIT-BIH arrhythmia database (MITDB), and it was verified by actual Holter ECG signals from a local hospital. The signals are classified into normal (N) and three arrhythmia beat types including premature ventricular contraction (PVC), ventricular flutter/fibrillation (VF), and second-degree heart block (BII) beat. This work produces 98.54% accuracy in the detection of R-wave location; 98.68% for N beats; 91.17% for PVC beats; and 87.2% for VF beats in the collected Holter ECG signals, and the results are better than what are reported in literature.

A facility layout design (FLD) problem can be generally introduced as assignment of facilities (departments) to a site such that a set of criteria are satisfied or some objectives are minimized (maximized). Hence, it can be considered as a multi-criteria problem due to the presence of qualitative criteria such as maintenance or flexibility and quantitative criteria such as the total cost of handling material. The VIKOR method was developed to solve multiple criteria decision making problems with conflicting and non-commensurable (different units) criteria, assuming that compromising is acceptable for conflict resolution, the decision maker wants a solution that is the closest to the ideal, and the alternatives are evaluated according to all established criteria. This paper proposes a hierarchical analytic hierarchy process (AHP) and VIKOR approach to solve the FLD problem. A computer-aided layout-planning tool is adopted to generate the facility layout problems, as well as their quantitative data. The qualitative performance measures are weighted by AHP. VIKOR is then used to solve the FLD problem. Finally, the proposed integrated procedure is applied to three real-time examples.

The present study examines a set of financial ratios in predicting the up or down movements of stock prices in the context of a securities law, the Sarbanes-Oxley Act of 2002 (SOA), controlling for macroeconomic variables. Using the logistic regression with proxy betas to alleviate the incompatibility problem between the firm-specific financial ratios and macroeconomic indicators, we report evidence that financial ratios are meaningful predictors of stock price changes, which subdue the influence of macroeconomic indicators on stock returns, and more importantly that the SOA truly improves the stock price predictability of financial ratios for the markup sample. The empirical results further suggest that industry and time effects exist and that for the markdown sample the SOA actually deteriorates the predictive power of financial ratios.