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At present, China’s industrial spatial layout faces the predicament of over-agglomeration of Eastern China industries and the near disintegration of industrial structure in the central and western regions. The paper aims to discuss this issue.

Based on the perspective of differentiated inter-regional labor mobility, this paper constructed a model framework of quadratic sub-utility quasi-linear preference utility function, and conducted model deduction and numerical simulation on causal factors of this spatial imbalance along the two dimensions of individual and regional welfare.

The study finds that in the long run, industrial spatial layout imposes a certain threshold limit on the portfolio proportion of differentiated labor. The dilemma of China’s industrial spatial layout is attributable to the deviation of the market’s optimal agglomeration from the social optimal agglomeration, and to the disfunction of Eastern China’s role as an intermediary between the global and the domestic value chain.

To resolve this predicament of industrial layout, the unitary welfare compensation based on fiscal transfer payment has to be switched to a more comprehensive approach giving consideration to industrial rebalancing.

Various approaches and algorithms have been proposed since the 1950s to solve the assembly line (AL) balancing problem. These methods have established an AL configuration from the beginning. However, a prebalanced AL may have to be rebalanced in real life for many reasons, such as changes in the cycle time, production demand, product features or task operation times. This problem has increasingly attracted the interest of scientists in recent years. This study aims to offer a detailed review of the assembly line rebalancing problems (ALRBPs) to provide a better insight into the theoretical and practical applications of ALRBPs.

A structured database search was conducted, and 41 ALRBP papers published between 2005 and 2022 were classified based on the problem structure, objective functions, problem constraints, reasons for rebalancing, solution approaches and type of data used for solution evaluation. Finally, future research directions were identified and recommended.

Single model, straight lines with deterministic task times were the most studied type of the ALRBPs. Eighteen percent of the studies solved worker assignment problems together with ALRBP. Product demand and cycle time changes were the leading causes of the rebalancing need. Furthermore, seven future research opportunities were suggested.

Although there are many review studies on AL balancing problems, to the best of the authors’ knowledge, there have been no attempts to review the studies on ALRBPs.

The product family assembly line (PFAL) is a mixed model-assembly line, which is widely used in mass customization and intelligent manufacturing. The purpose of this paper is to study the problem of PFAL, a flexible (evolution) planning method to respond to product evolution for PFAL, to focus on product data analysis and evolution planning method.

The evolution balancing model for PFAL is established and an improved NSGA_II (INSGA_II) is proposed. From the perspective of data analysis, dynamic characteristics of PFAL are researched and analyzed. Especially the tasks, which stability is considered, can be divided into a platform and individual task. In INSGA_II algorithm, a new density selection and a decoding method based on sorting algorithms are proposed to compensate for the lack of traditional algorithms.

The effectiveness and feasibility of the method are validated by an example of PFAL evolution planning for a family of similar mechanical products. The optimized efficiency is significantly improved using INSGA_II proposed in this paper and the evolution planning model proposed has a stronger ability to respond to product evolution, which maximizes business performance over an effective period of time.

The assembly line designers and managers in discrete manufacturing companies can obtain an optimal solution for PFAL planning through the evolution planning model and INSGA-II proposed in this paper. Then, this planning model and optimization method have been successfully applied in the production of small wheel loaders.

A new era of M&A is emerging, characterized by new wave of strategic investment decision-making practices (SIDMP) toward Industry 4.0 (I4.0) technologies and circular economy. The digital technologies play a significant role in circular economy transitions and companies’ performance This includes investment in capability development, vertical and horizontal integration, effective procurement practices, and effective strategic control mechanisms. The circular economy strategy is more than just recycling and environmental concerns. It unlocks new strategies and new ways of strategic thinking. Its rapid expansion, as a new norm for companies, has characteristics of a fast-expanding market, given its exponential growth. Yet, there is a need to boardrooms commitment and responsibilities including oversight and support and a full-integrated organizational structure, sales, logistics, marketing, production, development, design, supply management, finance, human resources, and legal. To achieve successful implementation of SIDMP and M&A, companies should gather information on environmental, social, and governance issues. Therefore, it is critical to prioritize their strategies and identify areas that present the greatest risk on environmental and social issues including human rights, labor, and ethical issues in the companies supply chain. By creating shared values between society and shareholders, companies can maintain long-term success, legitimacy, and credibility. This chapter offers debate on recent developments in research and practice regarding SIDMP and synergy between I4.0 and circular economy.

This study aims to propose a new multiobjective optimization metaheuristic based on the tiki-taka algorithm (TTA). The proposed multiobjective TTA (MOTTA) was implemented for a simple assembly line balancing type E (SALB-E), which aimed to minimize the cycle time and workstation number simultaneously.

TTA is a new metaheuristic inspired by the tiki-taka playing style in a football match. The TTA is previously designed for a single-objective optimization, but this study extends TTA into a multiobjective optimization. The MOTTA mimics the short passing and player movement in tiki-taka to control the game. The algorithm also utilizes unsuccessful ball pass and multiple key players to enhance the exploration. MOTTA was tested against popular CEC09 benchmark functions.

The computational experiments indicated that MOTTA had better results in 82% of the cases from the CEC09 benchmark functions. In addition, MOTTA successfully found 83.3% of the Pareto optimal solution in the SALB-E optimization and showed tremendous performance in the spread and distribution indicators, which were associated with the multiple key players in the algorithm.

MOTTA exploits the information from all players to move to a new position. The algorithm makes all solution candidates have contributions to the algorithm convergence.

The purpose of this paper is to explain the reasons and development trend of the new round of restructuring of regional division of labor in East Asia after the global financial crisis and the role of China in the process.

The paper probes into four factors leading to the adjustment of regional division of labor in East Asia before analyzing its development trend trough comparing the change of roles of China and ASEAN in the process.

After the flying-geese division and regional production network, East Asia’s regional division of labor is getting a new round of structural adjustment. The analysis of this paper shows that this adjustment is mainly due to global financial crisis, post-crisis de-globalization, the rebalancing of East Asian economies and China’s economic transformation. From the adjustment direction, the main trend is ASEAN gradually replacing China to become the new assembly plant area, while China becomes a new manufacturing power by its rising status in the global value chain.

The paper describes the development trend of the new round of restructuring of regional division of labor in East Asia in the future and gives the policy implications for the East Asian countries.

This paper examines global imbalance and rebalancing issues from the viewpoint of Korea. As IMF (2009) notes, the unwinding of global imbalance seems inevitable and, in fact, it is in progress. We illustrate that Korea, with a flexible exchange rate system and relatively balanced current accounts, has little direct linkage to global imbalance. However, we also find that Korea is not immune to the costly adjustment process of imbalance due to the triangular trade between Korea, China and the U.S. The fact that Korea is ‘indirectly’ linked to global imbalance limits Korea’s ability to cope with the situation. Boosting domestic demand, often mentioned recommendation for East Asia, is not an appropriate solution for Korea with low personal savings rate. A lot depends on China’s policy. If China reduces its dependence on U.S. market and increases domestic consumption despite unemployment risk in export manufacturing sector, it will provide Korea with an opportunity for more stable growth based on China’s final demand. Korea can also make efforts to increase economic integration and expand monetary cooperation in Asia that would help to increase consumption demands and final goods trade in the region.

This paper aims to propose an alternate, efficient and scalable modeling framework to simulate large-scale bike-sharing systems using discrete-event simulation. This study uses this model to evaluate several initial bike inventory policies inspired by the operation of the bike-sharing system in Mexico City, which is one of the largest around the world. The model captures the heterogeneous demand (in time and space) and this paper analyzes the trade-offs between the performance to take and return bikes. This study also includes a simulation-optimization algorithm to determine the initial inventory and present a method to deal with the bias caused by dynamic rebalancing on observed demand.

This paper is based on the analysis of an alternate and efficient discrete-event simulation modeling framework. This framework captures the heterogeneity of demand and allows one to experiment with large-scale models. This study uses this model to test several initial bike inventory policies and also combined them with an optimization engine. The results, provide valuable insights not only for the particular system that motivated the study but also for the administrators of any bike-sharing system.

The findings of this paper include: most of the best policies use a ratio of bikes: docks near to 1:2; however, it is important the way they are initially allocated; a policy that contradicts the demand profile of the stations can lead to poor performance, regardless the quick and dynamic changes of bike locations during the morning period; the proposed simulation-optimization algorithm achieves the best results.

The findings are limited to the initial inventory of the system under study. The model assumes a homogeneous probability distribution function for the travel time. This assumption seems reasonable for the system under study. This paper limits the tested inventory policies to simple practical rules. There might be other sophisticated methods to obtain better solutions, but they might be system-specific.

The insights of this paper are valuable for operators of bike-sharing systems because this study focuses on the analysis of the impact of the initial inventory assuming that dynamic rebalancing may not be existing during the morning peak-time. This paper finds that initial inventory has a great impact on the performance, regardless of how quickly the bikes are dispersed across the system. This study also provides insights into the effect of dynamic rebalancing on observed demand.

Increasing knowledge about the operation of the bike-sharing system has a positive effect on society because more cities around the world could consider implementing these systems as a public transportation mode. Furthermore, delivering suggestions on how to increase the user service level could incentivize people to adopt bikes as a mobility option, which would contribute to improve their health and also reduce air pollution caused by motorized vehicles.

This paper considers that the contributions of this work to existing literature are the following: this study proposes a novel efficient and scalable simulation framework to evaluate initial bike inventory policies; the analysis presented in the paper includes an approach to deal with the bias in the observed demand caused by dynamic rebalancing and the analysis includes the value of demand information to determine an effective initial bike inventory policy.