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Purpose – The chapter studies methods of integrating the connection between land use and traffic surrounding rail transit stations. It offers guidance to urban planners about how to arrange transfer facilities scientifically and promote more efficient use of land nearby.

Methodology – The chapter describes studies of station type, station positioning, recommended building floor area ratio (FAR), traffic connection and land use functional demand for five stations on No. 2 Metro Line in Nanjing, determining the traffic connections and layout for the land use surrounding the five stations.

Findings – This study of the integrated connection between land use and transport surrounding rail transit stations will act as a guide to help arrange the building of essential transfer facilities scientifically and help cities to make better use of the scarce amount of urban land available for development. This study also shows that the transport system plays an important part in adjusting the functional layout of land use surrounding rail transit stations.

Social implications – The results of this study will be particularly significant in the integration of urban planning management and transport management. Furthermore, the coordinated interaction between land-use planning, traffic planning and urban design will benefit Chinese cities as they continue to grow throughout the 21st century and beyond.

The paper aims to identify and analyze passengers’ riding paths for providing better operational support for digital transformation in megacity metro systems.

The authors develop a method to leverage certain passengers’ deterministic riding paths to corroborate other passengers’ uncertain paths. Using Automatic Fare Collection data and train schedules, a witness model is built to recover the actual riding paths for passengers whose paths are unknown otherwise. The identification and analysis of passenger riding paths between three different types of origin–destination) pairs reveal the complexity of passenger path choice.

The results show that passenger path choice modeling is usually characterized by complexity, experience and partial blindness. Some passengers choose paths that are not optimal due to their experience and limited access to overall metro system information. These passengers could be the subject of improved path guidance in light of riding efficiency improved through digital transformation.

This research contributes to the improvement of metro management and operations by leveraging ongoing digital transformation in megacity metro systems. Based on the riding paths and trip chains of a large number of individual passengers identified by the proposed method, metro operation management could prevent risks in areas with concentrated passenger flow in advance, optimally adjust train schedules on a daily basis and deliver real-time riding guidance station by station, which would greatly improve megacity metro systems’ service safety, quality and operational efficacy over time.

Many bike rental organizations permit customers to pick-up bikes from one bike station and return them at a different one. However, this service may result in bike imbalance, as bikes may accumulate in stations with low demand. To overcome the imbalance problem, this paper aims to develop a decision model to minimize the total costs of unmet demand and empty bike transport by determining bike fleet size, deployments and the vehicle routing schedule for bike transports.

This paper developed a constrained mixed-integer programming model to deal with this bike imbalance problem. The proposed model belongs to the non-deterministic polynomial-time (NP)-hard problem. This paper developed a two-phase heuristic approach to solve the model. In Phase 1, the approach determines fleet size, deployment level and the number of satisfied demands. In Phase 2, the approach determines the routing schedule for bike transfers.

Computational results show the following results that the proposed approach performs better than General Algebraic Modeling System (GAMS) in terms of solution quality, regardless of problem size. The objective values and the fleet size of rental bikes allocated increase as the number of rental stations increases. The cost of transportation is not directly proportional to the number of bike stations.

The authors provide an integrated model to simultaneously deal with the problems of fleet sizing, empty-resource repositioning and vehicle routing for bike transfer in multiple-station systems, and they also present an algorithm that can be applied to large-scale problems which cannot be solved by the well-known commercial software, GAMS/CPLEX.

Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail transit passengers during the epidemic. The purpose of this paper is to efficiently monitor the flow of rail passengers, the first method is to regulate the flow of passengers by means of a coordinated connection between the stations of the railway line; the second method is to objectively distribute the inbound traffic quotas between stations to achieve the aim of accurate and reasonable control according to the actual number of people entering the station.

This paper analyzes the rules of rail transit passenger flow and updates the passenger flow prediction model in time according to the characteristics of passenger flow during the epidemic to solve the above-mentioned problems. Big data system analysis restores and refines the time and space distribution of the finely expected passenger flow and the train service plan of each route. Get information on the passenger travel chain from arriving, boarding, transferring, getting off and leaving, as well as the full load rate of each train.

A series of digital flow control models, based on the time and space composition of passengers on trains with congested sections, has been designed and developed to scientifically calculate the number of passengers entering the station and provide an operational basis for operating companies to accurately control flow.

This study can analyze the section where the highest full load occurs, the composition of passengers in this section and when and where passengers board the train, based on the measured train full load rate data. Then, this paper combines the full load rate control index to perform reverse deduction to calculate the inbound volume time-sharing indicators of each station and redistribute the time-sharing indicators for each station according to the actual situation of the inbound volume of each line during the epidemic. Finally, form the specified full load rate index digital time-sharing passenger flow control scheme.

This study aims to improve the passenger accessibility of passenger demands in the end-of-operation period.

A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway, the minimum headway and the latest end-of-operation time. The objective of the model is to maximize the number of reachable passengers in the end-of-operation period. A solution method based on a preset train service is proposed, which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.

The results of the case study of Wuhan Metro show that the solution method can obtain high-quality solutions in a shorter time; and the shorter the time interval of passenger flow data, the more obvious the advantage of solution speed; after optimization, the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.

Existing research results only consider the passengers who take the last train. Compared with previous research, considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination. Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network, but due to the decrease in passenger demand, postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.

This paper addresses a location-routing problem (LRP) under uncertainty for providing emergency medical services (EMS) during disasters, which is formulated using a robust optimization (RO) approach. The objectives consist of minimizing relief time and the total cost including location costs and the cost of route coverage by the vehicles (ambulances and helicopters).

A shuffled frog leaping algorithm (SFLA) is developed to solve the problem and the performance is assessed using both the ε-constraint method and NSGA-II algorithm. For a more accurate validation of the proposed algorithm, the four indicators of dispersion measure (DM), mean ideal distance (MID), space measure (SM), and the number of Pareto solutions (NPS) are used.

The results obtained indicate the efficiency of the proposed algorithm within a proper computation time compared to the CPLEX solver as an exact method.

In this study, the planning horizon is not considered in the model which can affect the value of parameters such as demand. Moreover, the uncertain nature of the other parameters such as traveling time is not incorporated into the model.

The outcomes of this research are helpful for decision-makers for the planning and management of casualty transportation under uncertain environment. The proposed algorithm can obtain acceptable solutions for real-world cases.

A novel robust mixed-integer linear programming (MILP) model is proposed to formulate the problem as a LRP. To solve the problem, two efficient metaheuristic algorithms were developed to determine the optimal values of objectives and decision variables.

The purpose of this paper is to trace the historical development of gasoline service stations through to 1956, their quantitative importance, the principal types of stations in existence in 1956, and the nature of competition in the business.

A synthesis of historical work on the development of gasoline retailing to 1956 is combined with detailed analysis of US Census statistics covering the period from 1929 through the early 1950s. Beckman was in charge of the Census of Wholesale Distribution for the US Department of Commerce in 1930.

There was rapid and significant growth in the number of gasoline service stations from the early twentieth century through 1939. This, combined with the effects of the Depression and Second World War, led to intense competition, an increase in the lines of merchandise carried by service stations, and ultimately to a decline in the number of stations.

Beckman combined a fresh interpretation of earlier published research on the history of the oil industry with extensive original historical analysis of US Census data. The article's value is heightened in that it is excerpted from a rare unpublished archival document written by one of the eminent marketing scholars of the twentieth century. This article is a slightly edited version of the first of two sections of the original manuscript written by Beckman in 1956 but never published (Theodore Beckman Collection, RG 40/35/C, Ohio State University Archives). The second section of the original manuscript (not included in this article) deals with changes in merchandise lines and services as well as the factors leading to those changes. The article published here is done so with permission of the Ohio State University Archives.

Metro stations have become a crucial aspect of urban rail transportation, integrating facilities, equipment and pedestrians. Impractical physical layout designs and pedestrian psychology impact the effectiveness of an evacuation during a metro fire. Prior research on emergency evacuation has overlooked the complexity of metro stations and failed to adequately consider the physical heterogeneity of stations and pedestrian psychology. Therefore, this study aims to develop a comprehensive evacuation optimization strategy for metro stations by applying the concept of design for safety (DFS) to an emergency evacuation. This approach offers novel insights into the management of complex systems in metro stations during emergencies.

Physical and social factors affecting evacuations are identified. Moreover, the social force model (SFM) is modified by combining the fire dynamics model (FDM) and considering pedestrians' impatience and panic psychology. Based on the Nanjing South Metro Station, a multiagent-based simulation (MABS) model is developed. Finally, based on DFS, optimization strategies for metro stations are suggested.

The most effective evacuation occurs when the width of the stairs is 3 meters and the transfer corridor is 14 meters. Additionally, a luggage disposal area should be set up. The exit strategy of the fewest evacuees is better than the nearest-exit strategy, and the staff in the metro station should guide pedestrians correctly.

Previous studies rarely consider metro stations as sociotechnical systems or apply DFS to proactively reduce evacuation risks. This study provides a new perspective on the evacuation framework of metro stations, which can guide the designers and managers of metro stations.

The electronics industries are relying increasingly on robotics for their production. Wafer handling robots are used to transfer wafers between wafer processing stations. A pick‐measure‐place method is typically utilized to transfer wafers accurately. The measurement step is performed using an aligner, which is time‐consuming. To increase wafer transfer efficiency, it is desirable to speed up the measurement process or place it in parallel with other operations. To solve the problem, optic sensors are installed at each station to estimate the wafer eccentricity on‐the‐fly. The eccentricity values are then applied to control the robot to place the wafer directly onto another station accurately without using the aligner. However, current methods face problems to achieve high accuracy requirements to meet the electronic manufacturing needs. The purpose of this paper is to develop a technique to improve the wafer handling performance in semiconductor manufacturing.

The kinematics model of the wafer handling robot is developed. Two sensor location calibration algorithms are proposed. Method I is based on the wafer handling path. Method II uses the offset paths from the wafer handling path. The results from these two methods are compared. To compute the wafer eccentricity on‐the‐fly, a wafer eccentricity estimation technique is developed.

The developed methods are implemented using a wafer handling robotic system in semiconductor manufacturing. The wafer eccentricity estimation errors are greatly reduced using the developed methods. The experimental results demonstrate that Method II achieves better results and can be used to improve the wafer handling accuracy and efficiency.

The proposed technique is implemented and tested many times on a wafer handing robotic system. The notch alignment in the wafer handling needs further research.

The developed method is validated using a system in semiconductor manufacturing. Hence the developed method can be directly implemented in production if the notch of a wafer can be identified.

This paper provides techniques to improve the wafer handling accuracy in semiconductor manufacturing. Compared with the results using other methods, Method II greatly increases the wafer handling accuracy to satisfy the semiconductor manufacturing needs.

The chapter aims to evaluate the efficacy of stakeholder participation in the solid waste management system of Mauritius in view of providing a possible mechanism to attain the goals of a sustainable waste management framework.

The study employs qualitative indicators, namely, User Inclusivity and Producer Inclusivity of the Wasteaware Benchmark Indicators. Secondary data are used to conduct a critical and comprehensive analysis of the sub-indicators falling under each of the two main indicators to determine the overall compliance level with respect to stakeholder engagement of the waste management sector of Mauritius.

The results of the study show a LOW/MEDIUM compliance level for both User Inclusivity and Provider Inclusivity indicators, which indicates that improvement is required in the stakeholder engagement mechanism in Mauritius. The main weaknesses identified comprise of lack of an adequate legal framework with clear definition of waste types with regards to segregation, especially for non-hazardous wastes, low efficiency of sustainable waste management awareness campaigns and lack of inclusion of the informal sector. The main strengths identified consist of a proper bidding mechanism in place and a good level of equity in the provision of waste management services with respect to comingled waste collection. Suggested improvement areas include a revamping of the existing legal framework related to waste management to cater for higher inclusivity of all stakeholders together with including sustainable waste management topics in the formal education curriculum.

The User Inclusivity and Producer Inclusivity indicators were previously applied only to cities to measure the level of stakeholder participation, but this study has demonstrated that these indicators can also be adopted on a nation-wide level to evaluate stakeholder engagement. The use of these indicators together with secondary data presents a less time-consuming method to assess stakeholder participation in the waste sector, which can be particularly useful for Small Island Developing States.