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This study aims to examine the trend of industrial competition between the US and China, which is the most crucial determinant in the future development of the global economy. For decades, the global economy has strengthened the global production network based on the division of labor between countries. Thus, the ripple effect of competition between the two countries should be analyzed in terms of the global production network. Therefore, this study uses the product space model, which explains the development process of industries with comparative advantage by country. We constructed the model based on the products of HS 4-digit code for the 2010–2019 period. The analysis results on the trend of the industrial competitiveness of major countries are as follows. First, the current industrial competitiveness of China is concentrated on low-tech industries. In the case of high-tech items, China shows a tendency of lower export sophistication compared to major manufacturing powerhouses such as Germany, the US, Japan, and Korea. Second, with respect to the possibility of a future industrial structure upgrade evaluated by density, the trend of China overtaking other manufacturing powerhouses is observed. As implied by the product space model, the advancement of the industrial structure through active participation in international trade enhances the industrial competitiveness. Therefore, the outcome of US-China industrial competition depends on who ensures more openness and industrial complexity.

This paper considers the problem of deciding disassembly order quantity in a disassembly system. Returned end-of-use/life (EOL) products are disassembled to retrieve reusable parts sold to secondar...

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.

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.

This study addresses the problem of determining the ship speed and bunkering ports in a ship route. All of the previous research has investigated the ship speed optimization issues by assuming that the ship navigates at constant speed or by ignoring the bunkering port decision. In this study, the problem of determining the variable speed and bunkering port is formulated mathematically with a nonlinear program in order to minimize the bunker fuel, ship time costs, and carbon tax imposed on greenhouse gas emissions. This study then provides a Lagrangian heuristic by deriving a property for a relaxed problem. The performance of the heuristic is evaluated and analysed using the data obtained from the literature, real practice and random generation.

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...

This paper presents a case study on the problems which result when loading air containers onto DHL and Air Hong Kong air express carriers. Problems often arise when trying to determine which containers should be loaded and where the containers should be located in an aircraft in order for it to maintain stability. The objective of this activity is to maximize the revenue obtained from delivering containers. We will present an integer programming model which will attempt to optimally solve the problem. Computational experiments which have been done on a number of randomly generated test instances show that the integer programming model can be a viable tool for generating loading plans within the companies since optimal or near-optimal solutions were obtained during the test instances within a reasonable amount of computation time.

The strategic location of city logistics facilities may help to establish more efficient urban logistics systems, reduce social and environmental costs of urban freight transport, and improve urban traffic conditions. In addition, it may allow a number of shippers or freight carriers to jointly operate freight vehicles and terminals or information systems while allowing them to have the capability to provide higher levels of services to their customers. This paper considers the problem of selecting a location for a city logistics facility while considering linguistic factors. This paper identifies the important factors in the selection of a location for a city logistics facility by performing a case study which applies the analytic hierarchy process method on data from Chongqing, China. The optimal location in Chongqing is then determined by using the fuzzy synthetic evaluation method. The results of this paper are expected to help municipal governments select appropriate locations for city logistics facilities and quantify the advantages and disadvantages of alternative locations.

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 ...

Dynamic lot sizing is the problem of determining the quantity and timing of ordering items while satisfying the demand over a finite planning horizon. This paper considers the problem with two practical considerations: minimum order size and lost sales. The minimum order size is the minimum amount of items that should be purchased and lost sales involve situations in which sales are lost because items are not on hand or when it becomes more economical to lose the sale rather than making the sale. The objective is to minimize the costs of ordering, item , inventory holding and lost sale over the planning horizon. To solve the problem, we suggest a heuristic algorithm by considering trade-offs between cost factors. Computational experiments on randomly generated test instances show that the algorithm quickly obtains near-optimal solutions.

This paper considers disassembly scheduling, which is the problem of determining the quantity and timing of the end-of-use/life products to be disassembled while satisfying the demand for their parts obtained from disassembling the products over a planning horizon. This paper focuses on the problem with stochastic demand of parts/modules, capacity restrictions on disassembly resources, and multiple product types with a two-level product structure. The two-level product structure implies that an end-of-use/life product is hierarchically decomposed into two levels where the first level corresponds to the parts/modules and the second level corresponds to the product. We formulate the problem as a stochastic inventory model and to solve the problem we propose a Lagrangian heuristic algorithm as well as an optimisation algorithm for the sub-problems obtained from Lagrangian decomposition. The test results on randomly generated problems show that the Lagrangian heuristic algorithm demonstrates good performance in terms of solution quality and time.

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.

This paper considers the problem of determining the disassembly schedule (quantity and timing) of products in order to satisfy the demand of their parts or components over a finite planning horizon. The objective is to minimize the sum of set-up, disassembly operation, and inventory holding costs. As an extension of the uncapacitated versions of the problem, we consider the resource capacity restrictions over the planning horizon. An integer program is suggested to describe the problem mathematically, and to solve the problem, a heuristic is developed using a Lagrangean relaxation technique together with a method to find a good feasible solution while considering the trade-offs among different costs. The effectiveness of the algorithm is tested on a number of randomly generated problems and the test results show that the heuristic suggested in this paper can give near optimal solutions within a short amount of computation time.

Disassembly scheduling is one of the important planning problems in disassembly systems, and generally defined as the problem of determining the quantity and timing of disassembling products in order to satisfy the demand of their parts or components over a planning horizon. This paper focuses on the case of multiple product types with parts commonality for the objective of minimizing the sum of set-up, disassembly operation and inventory-holding costs, and it suggests a two-phase heuristic in which an initial solution is obtained using a linear-programming relaxation, and then improved by perturbing the initial solution using a dynamic programming algorithm with look-ahead check. Computational experiments are done on a number of randomly generated test problems and the results show that the heuristic suggested in this paper can give near-optimal solutions within a short computation time.

This paper focuses on an arc-welding robot scheduling problem, which is the problem of determining the sequence of welding operations while avoiding heat-caused distortion for the objective of minimizing the time required to complete a given set of welding operations. Each welding operation is specified by a weld line with two end points, each of which can be a possible starting point of the welding operation for that weld line. Because of the heat-caused distortion, there must be a certain period of time (delay) between welding operations associated with weld lines near each other. We develop several heuristic algorithms, in which heuristics for the travelling salesman problem are modified to cope with characteristics of the problem considered here. To show the performance of the heuristics suggested in this paper, computational experiments are performed on a number of randomly generated test problems and results are reported.

This paper addresses the problem of determining the ship speed, fleet size, and chartered ship number subject to environmental regulations consisting of a carbon tax and an emission trading scheme. The objective of the problem is to minimise bunker consumption cost, ship operating cost, ship charterage and either the carbon tax or the revenue/cost of selling/purchasing CO2 emissions permits. We formulate the problems as non-linear programmes by considering the two regulations independently. This study also suggests Lagrangian heuristics to solve the problems. A case study is performed to evaluate the applicability of the heuristics.