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It is highly challenging to measure the efficiency of electric vehicle charging stations (EVCSs) because factors affecting operational characteristics of EVCSs are time-varying in practice. For the efficiency measurement, environmental factors around the EVCSs can be considered because such factors affect charging behaviors of electric vehicle drivers, resulting in variations of accessibility and attractiveness for the EVCSs. Considering dynamics of the factors, this paper examines the technical efficiency of 622 electric vehicle charging stations in Seoul using data envelopment analysis (DEA). The DEA is formulated as a multi-period output-oriented constant return to scale model. Five inputs including floating population, number of nearby EVCSs, average distance of nearby EVCSs, traffic volume and traffic congestion are considered and the charging frequency of EVCSs is used as the output. The result of efficiency measurement shows that not many EVCSs has most of charging demand at certain periods of time, while the others are facing with anemic charging demand. Tobit regression analyses show that the traffic congestion negatively affects the efficiency of EVCSs, while the traffic volume and the number of nearby EVCSs are positive factors improving the efficiency around EVCSs. We draw some notable characteristics of efficient EVCSs by comparing means of the inputs related to the groups classified by K-means clustering algorithm. This analysis presents that efficient EVCSs can be generally characterized with the high number of nearby EVCSs and low level of the traffic congestion.

The air transportation industry is one big network that is expected to grow continuously, and Asia-Pacific is the fastest growing region as of 2018 data. We apply weighted network analysis to explore the key network characteristics of the Asian international passenger aviation market in 2014 and 2018. For the analysis, networks are constructed based on international passengers' origin-destination pair data from 28 Asian airlines in 2014 and 2018. Previously published social network analysis (SNA) on the air transportation network largely used unweighted centrality metrics, whereas the actual situation is a weighted network. We implement Mean Associations (MA), Triangle Betweenness Centrality (TBC), and Weighted PageRank (WPR), as new weighted centrality metrics, to effectively reflect actual passenger traffic among airports beyond simple connections. Our weighted network analysis indicates that SIN, ICN, HKG, NRT, MNL, BKK, TPE, HND, PEK, and KUL are the top-ranked hub airports, followed by SGN, PVG, CAN, DEL, SYD, KIX and CGK, and that the low-cost carriers have almost fully developed a ‘hub-and-spoke’ structure over the 4-year study period and are increasing their impact on the centrality of airports in the region.

Evaluating the operational efficiency of electric vehicle charging stations (EVCSs) is important to understand charging network evolution and the charging behavior of electric vehicle users. However, aggregation of efficiency performance metrics poses a significant challenge to practitioners and researchers. In general, the operational efficiency of EVCSs can be measured as a complicated function of various factors with multiple criteria. Such a complex aspect of managing EVCSs becomes one of the challenging issues to measure their operational efficiency. Considering the difficulty in the efficiency measurement, this paper suggests a way to measure the operational efficiency of EVCSs based on data envelopment analysis (DEA). The DEA model is formulated as constant returns of output-oriented model with five types of inputs, four of them are the numbers of floating population and nearby charging stations, distance of nearby charging stations and traffic volume as desirable inputs and the other is the traffic speed in congestion as undesirable one. Meanwhile, the output is given by the charging frequency of EVCSs in a day. Using real-world data obtained from reliable sources, we suggest operational efficiencies of EVCSs in Seoul and discuss implications on the development of electric vehicle charging network. The result of efficiency measurement shows that most of EVCSs in Seoul are inefficient, while some districts (Nowon-gu, Dongdaemun-gu, Dongjak-gu, Songpa-gu, Guro-gu) have relatively more efficient EVCSs than the others.

In today’s multi-channel distribution environment, it is crucial for the competitiveness of retail stores and companies to improve efficiency of dedicated logistics centers (DLCs) servicing types of retail outlets such as large retail-stores, super supermarkets, and convenient stores. This paper derives efficiency improvement strategies for DLCs through efficiency analyses. To this end, this paper empirically analyzes the efficiency of DLCs by applying DEA (data envelopment analysis) approaches using real data from a Korean distribution company. In detail, this paper analyzes operations, finance, and service efficiencies of DLCs and performs a comparison analysis on the efficiency between DLCs. Finally, this paper discusses the analysis results considering the DLCs’ characteristics and derives managerial and operational implications.

In South Korea, Jeju Island has a role as a test bed for electric vehicles (EVs). All conventional cars on the island are supposed to be replaced with EVs by 2030. Accordingly, how to effectively set up EV charging stations (EVCSs) that can charge EVs is an urgent research issue. In this paper, we present a case study on planning the locations of EVCS for Jeju Island, South Korea. The objective is to determine where EVCSs to be installed so as to balance the load of EVCSs while satisfying demands. For a public service with EVCSs by some government or non-profit organization, load balancing between EVCS locations may be one of major measures to evaluate or publicize the associated service network. Nevertheless, this measure has not been receiving much attention in the related literature. Thus, we consider the measure as a constraint and an objective in a mixed integer programming model. The model also considers the maximum allowed distance that drivers would detour to recharge their EV instead of using the shortest path to their destination. To solve the problem effectively, we develop a heuristic algorithm. With the proposed heuristic algorithm, a variety of numerical analysis is conducted to identify effects of the maximum allowed detour distance and the tightness of budget for installing EVCSs. From the analysis, we discuss the effects and draw practical implications.

Owing to growing economic growth in tandem with regional economic developments on the route connecting Asia and sub-Saharan Africa (SSA), several countries in the SSA region such as South Africa have been developing container ports. This paper analyzes potential trunk line routes and transshipment flows that could be captured by potential hub ports in the SSA region. To this end, integer programing models are developed to represent liner shipping networks in the SSA region and a wide variety of numerical experiments based on realistic data are conducted for the SSA-Europe and SSA-Asia trade routes. This paper draws various meaningful policy and managerial implications through scenario analyses such as the effects of network evolution, different vessel sizes and speeds, carbon taxes and insights in association with the 21st Century Maritime Silk Road initiated by China.

This paper discusses a case of truck sharing as an application of the sharing economy. This case study examines a real mixed feed company with multiple factories. In this company’s operation, bulk trucks located in a factory had not previously been shared for delivery with other factories to their pre-assigned customers of stock farms. Therefore, this paper suggests a new delivery system that facilitates truck-sharing and analyzes its effects on the transport cost and trucks’ CO2 emissions. To this end, this paper develops vehicle routing models to represent the current delivery practice and the new truck-shared delivery (TSD). In addition, models are developed for a carbon control policy of an emission trading scheme (ETS) and the effects of the ETS on truck-sharing are investigated. Numerical analysis is conducted to identify the effects of the TSD and the carbon control policy and draw practical implications.

Owing to high fuel costs and environmental regulations, the optimization of ship speed to minimize fuel consumption and reduce carbon emissions has become a hot issue in the maritime industry. In this paper, we study the sailing speed optimization problem for a ship operating on a route having a specified sequence of calling ports with time windows for calling time. The considered problem can be formulated as a non-linear program. We derive the intrinsic properties of the problem and develop an optimal algorithm based on the properties. Computational experiments show that the developed algorithm in this paper is efficient in finding an optimal solution.

In semiconductor wafer fabrication facilities, order-lot pegging is the process of assigning wafer lots to orders and meeting the due dates of orders is considered one of the most important operational issues. In many cases of order-lot pegging, some orders cannot be fulfilled with the current wafers in the lots being processed, necessitating the release of additional new wafer lots into the wafer fabrication facility. In this paper, we propose a simultaneous decision model for order-lot pegging and wafer release planning in semiconductor wafer fabrication facilities, and develop a Lagrangian heuristic for solving the model. The results of computational experiments conducted using randomly generated problem instances that mimic actual field data from a Korea semiconductor wafer fabrication facility indicate that the performance of the Lagrangian heuristic is superior to that of a practical greedy algorithm for practical-sized problem instances. The results also point to how sensitivity analysis can be use...

We study the ship speed optimization problem with the objective of minimizing the total fuel consumption. We consider multiple time windows for each port call as constraints and formulate the problem as a nonlinear mixed integer program. We derive intrinsic properties of the problem and develop an exact algorithm based on the properties. Computational experiments show that the suggested algorithm is very efficient in finding an optimal solution.

This paper provides an algorithm to minimize the fixed ordering, purchase, and inventory-carrying costs associated with bunker fuel together with ship time costs; and environmental costs associated with greenhouse gas emissions. It determines the optimum ship speed, bunkering ports, and amounts of bunker fuel for a given ship’s route. To solve the problem, we use an epsilon-optimal algorithm by deriving a property. The algorithm is illustrated by applying it to typical sample data obtained and the effects of bunker prices, carbon taxes, and ship time costs on the ship speed are analyzed. The results indicate that the ship speed and CO2 emissions are highly sensitive to the factors considered.

H maritime company in Korea had a long history of difficulty in obtaining enough empty containers to transport its commodities. Despite efforts to resolve the problem, the repositioning of empty containers between depots was still planned manually, which consumed much worker time. To automate the generation of reposition plans, we developed a planning system to optimize the company’s reposition of empty containers between global depots with a linear programming model functioning as a key decision engine in the system. The model determines the route, volume and mode of transportation for repositioning empty containers from depots with surplus containers to those requiring containers, as well as the empty space of ships generated from the unloading or loading of full and empty containers. The system has been in operation in the company’s global network since March 2008.

We consider the problem of determining the lot sizes that satisfy the demands of remanufactured products over a given planning horizon with discrete time periods. Remanufacturing, in which used or end-of-life products are restored to like-new condition, typically consists of disassembly, reprocessing and reassembly processes, and hence the lot sizes are determined for each of the three processes. The objective is to minimise the sum of setup and inventory holding costs occurring at the three processes. To represent the problem mathematically, we suggest a mixed integer programming model by combining the existing ones for disassembly and assembly systems. After proving that the problem is NP-hard, we suggest two dynamic programming based heuristics, called the aggregation and the decomposition type heuristics in this paper. Computational experiments were done on various test instances, and the results show that the two heuristics give near-optimal solutions in a short amount of computation time. Also, the ...

To alleviate harm to the environment, short sea shipping (SSS) is gaining popularity in transportation policy formulation as an alternative transport mode for ecofriendly and cost-efficient transportation. There have been no studies of how to optimize intermodal container movement incorporating environmental aspects into SSS networks. This paper analyzes an intermodal transportation problem of international container cargoes while incorporating the external costs of the modes into an optimization model in South Korea. The objective of the problem is to minimize the total logistic costs, that is, shipping and land transportation costs, as well as external costs such as air pollutants (particulate matter, nitrogen oxide, sulfur dioxide, and volatile organic compounds) and greenhouse gases (carbon dioxide). The results of the model show a strong foundation for encouraging more environmentally friendly modes, such as SSS and rail, and a well-balanced modal shift if transport policy is formulated in this direction.

Disassembly scheduling, one of the important operational problems in disassembly systems, can be generally defined as the problem of determining the quantity and timing of the end-of-use/life products while satisfying the demand of their parts over a planning horizon. This paper presents a literature review on this planning problem in disassembly systems. First, the basic form of the problem is defined with a mathematical formulation. To characterize the differences between assembly and disassembly processes, the effects of the divergence property are also explained with respect to the zero inventory property, indispensable surplus inventory, and mathematical representation. Then, we review the existing research articles on the basic problem and its generalizations. A systematic scheme for classifying problems is also suggested. Finally, we suggest several future research directions.