Marrying supply chain sustainability and resilience: A match made in heaven

Sustainable supply chain management has become an integral part of corporate strategy for virtually every industry. However, little is understood about the broader impacts of sustainability practices on the capacity of the supply chain to tolerate disruptions. This article aims to explore the sustainability–resilience relationship at the supply chain design level. A multi-objective optimization model featuring a sustainability performance scoring method and a stochastic fuzzy goal programming approach is developed that can be used to perform a dynamic sustainability tradeoff analysis and design a “resiliently sustainable” supply chain. Important managerial and practical insights are obtained from an empirical case study.     

Optimizing transit maintenance and rehabilitation to support human development and sustainability: A case study of Costa Rica’s railroad network

Public transportation plays a critical role in improving human development and consequently the 17 Sustainable Development Goals (SDGs) set by United Nations. Convenient and efficient transit enable inhabitants to reach labor markets, access social support facilities as well as health and education services. This study develops a decision-making support framework for transit agencies to select optimum maintenance, rehabilitation, and upgrade alternatives to accomplish good levels of service and improve human development and sustainability indexes. A case study of Costa Rica’s great metropolitan area is used to illustrate the study with various budget scenarios. The results show that the proposed system can accomplish significant improvements on both level of service and human development. It is also confirmed that the explicit consideration of human development and sustainability made a significant difference as compared to the classical approach, which only considers the level of service (LOS). The proposed model could be used by other public transit systems.     

An utility-based decision support sustainability model in slow steaming maritime operations

This paper analyses slow steaming sustainability initiatives and generalizes the traditional discrete cost-based decision support model into novel continuous utility-based models. Two models based on logarithmic and linear utility functions are developed for risk-averse and risk-neutral decision makers respectively. The models, considering fuel consumption, carbon emission, and on time delivery, are applied to a Trans-pacific trade service route. A sensitivity analysis is conducted on parameters of sailing distance, expected transit time, quantity, and emission policies. The model contributes to ship liners on the optimal speed decisions in continuous utility-based slow steaming operations.     

The new narrative of accessibility: its potential contribution to discourses in (transport) geography

A new narrative of accessibility has been incorporated into policy discourses in Great Britain. The paper’s aim is to contribute to the welcome debate in transport geography which concerns itself with accessibility and its potential relation with wider discourses, particularly those of sustainability, globalisation and new mobilities. The paper offers thoughts on the extent to which accessibility may have a role in this debate. It is argued that a fuller conceptualisation of accessibility has the potential to achieve fuller understandings of accessibility-based policy goals and their implications, as well as informing the design of instruments to achieve policy delivery. To this end, notions of ‘universal’ and ‘relative’ rights are summarised and discussed in the accessibility context. A simple notional system is proposed through which the roles in accessibility of these two ‘types’ of rights may be recognised and understood. It is also proposed that a concept of ‘strong’ and ‘weak’ accessibility, paralleling similar ideas of sustainability, can be of value in the design of policy aimed at achieving greater accessibility and hence social inclusion and social dimensions of sustainability. The potential for a fruitful conceptual interaction between an accessibility narrative and discourses of globalisation and new mobilities is explored with a view to stimulating debate.     

Sustainability evaluation of rapid routes for buses with a network DEA model

This study establishes a network data envelopment analysis (DEA) model to evaluate the sustainability of public transportation services targeting rapid routes for buses in the Seoul metropolitan area. A network DEA-based optimization model is formulated to evaluate the sustainability of the public transportation service. By considering public transportation services from both the operators’ and users’ perspectives, this model produces results that reflect the interaction of three sustainable transport service properties, i.e., efficiency, equity, and environmental impacts. It is identified that the expansion of median bus lanes and the conversion of conventional buses into compressed natural gas vehicles could improve the sustainability of the public transportation services in the Seoul metropolitan area. Some limitations and future research agenda also are presented.     

A robust optimization approach to the integrated berth allocation and quay crane assignment problem

This paper investigates the integrated berth allocation and quay crane assignment problem in container terminals. A deterministic model is formulated by considering the setup time of quay cranes. However, data uncertainties widely exist, and it may cause the deterministic solution to be infeasible. To handle the uncertainties, a robust optimization model is established. Furthermore, to control the level of conservativeness, another robust optimization model with the price constraints is proposed. A genetic algorithm and an insertion heuristic algorithm are suggested to obtain near optimal solutions. Computational experiments indicate that the presented models and algorithms are effective to solve the problems.     

Reliable design of an integrated supply chain with expedited shipments under disruption risks

This paper studied the design of a two-echelon supply chain where a set of suppliers serve a set of terminals that receive uncertain customer demands. In particular, we considered probabilistic transportation disruptions that may halt product supply from certain suppliers. We formulated this problem into an integer nonlinear program to determine the optimal system design that minimizes the expected total cost. A customized solution algorithm based on Lagrangian relaxation was developed to efficiently solve this model. Several numerical examples were conducted to test the proposed model and draw managerial insights into how the key parameters affect the optimal system design.     

Multi-objective design of an organ transplant network under uncertainty

We propose a novel multi-period location–allocation model for the design of an organ transplant transportation network under uncertainty. The model consists of a bi-objective mathematical programming model that minimizes total cost and time, including waiting time in the queue for the transplant operation, while considering organs’ priorities. A fuzzy multi-objective programming based approach is presented to solve the small and medium size problems to optimality. For larger problems, we propose two meta-heuristics based algorithms. Lower bounds, and several numerical examples with managerial insights are discussed. A real case-study is provided, and the existing and the proposed optimal solutions are compared.     

Storage pricing strategies for import container terminals under stochastic conditions

This paper presents a model for determining the optimal storage pricing schedule for import containers. A generic schedule which is characterized by a flat rate and a storage time charge is adopted. The model considers analytically the stochastic behavior of the storage yard, as input/output flows are random variables, and includes the migration to an off-dock warehouse. Two objective functions are proposed: maximizing terminal operator profits and minimizing total integrated cost of the system. Some numerical experiments are provided and a sensitivity analysis is performed to investigate the effect of main variables and approaches on the optimal solution.     

A supporting station model for reliable infrastructure location design under interdependent disruptions

This paper proposes a new modeling method that equivalently transforms interdependent and correlated facility failures in an infrastructure system into only i.i.d. disruptions in a supporting structure. The properties of this structure are examined and a mathematical model is created to solve reliable facility location design problems under correlated facility failure risks. This model is formulated into a compact integer linear program and can be efficiently solved by state-of-the-art solvers. A set of experiments and case studies are conducted to demonstrate the applicability of the proposed model and to draw managerial insights into the optimal system design.     

Space allocating strategies for improving import yard performance at marine terminals

This paper focuses on the organization of the import storage yard at container port terminals. Three new stacking strategies are introduced which take into account the containers’ arrival and departure rates and the storage yard characteristics. A mathematical model based on probabilistic distribution functions is developed to estimate the number of rehandles required to manage an import container yard. The model is applied to the three proposed stacking strategies. Results show that the optimal strategy depends on stacking height and the relationship between vessel headway and container dwell time.     

Optimal assignment of aircrew trainees to simulator and classroom training sessions subject to seniority and preference restrictions

We develop an integer programming model and an exact solution methodology for assigning aircrew members to training sessions which they need to attend in order to fulfill the requirements for renewal of their flight capability. The aim is to find the optimal assignment that minimizes the number of unassigned trainees, while also satisfying a variety of seniority, preference, capacity and language compatibility restrictions. The proposed methodology partitions the aircrew members into distinct groups based on their seniority, making the optimal assignment decisions pertaining to each of these groups sequentially. We present extensive computational results demonstrating that the proposed methodology enables the solution of realistic size problems in moderate computational times.     

An integrated modeling framework for design of logistics networks with expedited shipment services

This paper studied an integrated logistics network problem that determines optimal supplier locations, assignments of these suppliers to terminal facilities, expedited shipment configurations, and inventory management strategies in an uncertain environment. We studied the problem structure and proposed mathematical models to determine the optimal network design that minimizes the expected total system cost. We developed a customized solution approach based on Lagrangian relaxation that can solve these models efficiently and accurately. Numerical examples are conducted to draw managerial insights into how problem settings and key parameter values affect the optimal design results.     

Optimizing shipment,ordering and pricing policies in a two-stage supply chain with price-sensitive demand

In this paper we focus on a two-stage supply chain consisting of one vendor and one buyer. We develop an integrated production–inventory–marketing model to determine the relevant profit-maximizing decision variable values. The model proposed is based on the joint total profit of both the vendor and the buyer, and it finds out the optimal ordering, shipment and pricing policies. We are able to ascertain the optimal decision variable values employing an analytical solution procedure. The numerical evidence suggests that it is more beneficial for the buyer and the vendor to cooperate with each other when the demand is more price sensitive.     

Sustainability in Chinese development tourism policies

Following the ‘Open Door’ policy of 1978 that accepted tourism as an appropriate sector for development in China for the first time since 1949, national and local governments have issued policies to promote tourism. Over the past two decades, the continuing development of tourism has occurred as China has started to move towards sustainability in its national policies. Although sustainability is often stated as the purpose of development, and tourism development strategies are regarded as more environmentally oriented than other industries, little guidance is provided to make sure that sustainability principles are followed. To examine this situation, sustainability components in the two types of tourism policies are examined, including 56 tourism development policies by the state councils and 31 provinces since the 1980s. These indicate a mixed result. While sustainability is an important component in some of these policies, the meaning of sustainability in the tourism sector is confusing and pro-business tourism development still plays a dominant role. It is suggested a pro-active sustainability approach should be integrated with environmental concerns in the future to allow tourism to participate constructively in the national transformation to a sustainable society.     

A hedging policy for carriers’ selection under availability and demand uncertainty

We address a stochastic dynamic distribution problem where a family of products needs to be shipped from a warehouse to a distribution center (DC). Uncertainty is on carriers’ availability and demand at the DC. Internal, external and spot carriers must be optimally selected to minimize the expected discounted cost of transportation, inventories and shortages. We numerically prove that an optimal selection policy, SDMBSP, is based on three thresholds of the available inventory in the DC. A simulation model is proposed and proves the robustness of the SDMBSP and its outperformance over two other carrier selection policies.     

Unveiling large-scale commuting patterns based on mobile phone cellular network data

In this study, with Estonia as an example,we established an approach based on Hidden Markov Model to extract large-scale commuting patterns at different geographical levels using a massive amount of mobile phone cellular network data, which is referred to as Call detail record (CDR). The proposed model is designed for reconstructing and transforming the trajectories extracted from the CDR data. This step allowed us to perform origin-destination matrix extraction among different geographical levels, which helped in depicting the commuting patterns. Besides, we introduced different techniques for analyzing the commuting at the urban level. Our results unveiled that there is great potential behind mobile data of the cellular networks after transforming it into meaningful mobility patterns. That can easily be used for understanding urban dynamics, large-scale daily commuting and mobility. The aggressive development and growth of ubiquitous mobile sensing have generated valuable data that can be used with our approach for providing answers and solutions to the growing problems of transportation, urbanization and sustainability.     

Integrated recovery of aircraft and passengers after airline operation disruption based on a GRASP algorithm

This paper considers the integrated recovery of both aircraft routing and passengers. A mathematical model is proposed based on both the flight connection network and the passenger reassignment relationship. A heuristic based on a GRASP algorithm is adopted to solve the problem. A passenger reassignment solution is demonstrated to be optimal in each iteration for a special case. The effectiveness of the heuristic is illustrated through experiments based on synthetic and real-world datasets. It is shown that the integrated recovery of flights and passengers can decrease both the recovery cost and the number of disrupted passengers.     

Optimal delivery service strategy for Internet shopping with time-dependent consumer demand

This study attempts to optimize a delivery service strategy for Internet shopping by considering time-dependent consumer demand, demand–supply interaction and consumer socioeconomic characteristics. A nonlinear mathematical programming model is formulated for solving the optimal number and duration of service cycles for discriminating strategy by maximizing profit subject to demand–supply interaction. An example is employed to demonstrate the application of the model. Results suggest that discriminating service strategy is a better strategy in response to time-dependent consumer demand than uniform strategy. Finally, the proposed model is demonstrated to yield more profit than models that do not consider variations in consumer demand or demand–supply interaction.