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The purpose of this paper is to develop a method for diagramming a base camp or space for emergency workers and a staging area to be used during sorting, storing, loading, and unloading of relief goods in a humanitarian logistics base airport.

A method is developed based on a synthesis of the relevant literature and current practices of airports. This provides a means for estimating the area required for each facility and visualizes the layout of the base through an adjacency diagram and a bubble diagram. The method is applied to the Shizuoka Airport in Japan as a case study.

The proposed method can be used to determine the approximate size and layout of a humanitarian logistics base in an airport based on the affected population and the number of emergency workers.

Airport operation regulations and mathematical models from architectural planning need to be reflected further.

The method provides potential operational improvements for policies and standards for airport operations and enables government officials and humanitarian logistics organizations to identify concerns in facilitating and managing constraints in existing airports.

This study addresses the detailed phases in a diagramming for a humanitarian logistics base airport by integrating an architectural approach and airport disaster management. The results highlight the importance of managing the flexible use of space to improve effective humanitarian logistics.

The purpose of this paper is to reveal the importance of the order of establishment of temporary logistics hubs (TLHs) when resources (mobile storage units used as TLHs) are limited and to present the development and implementation of a methodology that determines the order of establishment of TLHs to support post-disaster decision making.

It employed a decision support system that considers multiple decision makers and subjective attributes, while also addressing the impreciseness inherent in post-disaster decision making for ordering the establishment of TLHs. To do so, an optimization model was combined with a fuzzy multi-attribute group decision making approach. A numerical illustration was performed using data from the April 2015 Nepal Earthquake.

The results showed the location and order of establishment of TLHs, and demonstrated the impact of decision makers’ opinions on the overall ordering.

The study does not discuss the uncertain nature of the location problem and the potential need for relocation of TLHs.

This methodology offers managerial insights for post-disaster decision making when resources are limited and their effective utilization is vital. The results highlight the importance of considering the opinions of multiple actors/decision makers to enable coordination and avoid complication between the growing numbers of humanitarian responders during disaster response.

This study introduces the concept of the order of establishment of TLHs and demonstrates its importance when resources are limited. It develops and implements a methodology determining the order of establishment of TLHs to support post-disaster decision making.

The purpose of this study is to develop a methodology which amalgamates quantitative and qualitative approaches to determine the best placement of mobile logistics hubs (MLH) to be established in different parts of Nepal as a part of real-life project, “Augmentation of National and Local-Level Emergency Logistics Preparedness in Nepal” (2017–2020), implemented by the World Food Programme in cooperation with the Government of Nepal.

The study develops a methodology using a combination of a modified version of the maximal covering location problem (MCLP) and focus group discussion. The MCLP model is used to determine the optimal number and spatial location of MLHs, and focus group discussion is used to identify the five first-priority strategic MLH locations using expert knowledge.

The authors identify the five first-priority locations for establishing MLHs using an amalgamation of quantitative approach (mathematical model) and qualitative approach (focus group discussion). By amalgamating mathematical model with expert knowledge, findings acceptable to a wide range of stakeholders are obtained. The focus group discussion helps to pinpoint the location of MLHs to city-level granularity which is otherwise impossible with data available on hand.

Although multiple experts’ judgements were obtained via focus group discussion, subjectivity and possible bias is inevitable. Overall, the quantitative results of the study are purely based on the data available during the study period; therefore, having updated data could possibly improve the quality of the results.

This study is the first of its kind that uses an amalgamation of mathematical model and expert knowledge to determine the strategic locations of MLHs and has been successful to an extent that the selected locations have been vetted by the government of Nepal for establishing MLHs and are undergoing implementation in real life. This study also considers multiple disaster scenarios and employs the concepts of human development, disaster risk and transportation accessibility to reflect Nepal's socioeconomic, geo-climatic and topographical features.

The purpose of this paper is to develop a mathematical model that determines the location of temporary logistics hubs (TLHs) for disaster response and proposes a new method to determine weights of the objectives in a multi-objective optimization problem. The research is motivated by the importance of TLHs and the complexity that surrounds the determination of their location.

A multi-period multi-objective model with multi-sourcing is developed to determine the location of the TLHs. A fuzzy factor rating system (FFRS) under the group decision-making (GDM) condition is then proposed to determine the weights of the objectives when multiple decision makers exist.

The interview with decision makers shows the heterogeneity of decision opinions, thus substantiating the importance of GDM. The optimization results provide useful managerial insights for decision makers by considering the trade-off between two non-commensurable objectives.

In this study, decision makers are considered to be homogeneous, which might not be the case in reality. This study does not consider the stochastic nature of relief demand.

The outcomes of this study are valuable to decision makers for relief distribution planning. The proposed FFRS approach reveals the importance of involving multiple decision makers to enhance sense of ownership of established TLHs.

A mathematical model highlighting the importance of multi-sourcing and short operational horizon of TLHs is developed. A new method is proposed and implemented to determine the weights of the objectives. To the best of the authors’ knowledge, the multi-actor and multi-objective aspects of the TLH location problem have not thus far been considered simultaneously for one particular problem in humanitarian logistics.

The purpose of this paper is to investigate the application of the dynamic vehicle routing problem for last mile distribution during disaster response. The authors explore a model that involves limited heterogeneous vehicles, multiple trips, locations with different accessibilities, uncertain demands, and anticipating new locations that are expected to build responsive last mile distribution systems.

The modified simulated annealing algorithm with variable neighborhood search for local search is used to solve the last mile distribution model based on the criterion of total travel time. A dynamic simulator that accommodates new requests from demand nodes and a sample average estimator was added to the framework to deal with the stochastic and dynamicity of the problem.

This study illustrates some practical complexities in last mile distribution during disaster response and shows the benefits of flexible vehicle routing by considering stochastic and dynamic situations.

This study only focuses day-to-day distribution on road/land transportation for distribution, and additional transportation modes need to be considered further.

The proposed model offers operational insights for government disaster agencies by highlighting the dynamic model concept for supporting relief distribution decisions. The result suggests that different characteristics and complexities of affected areas might require different distribution strategies.

This study modifies the concept of the truck and trailer routing problem to model locations with different accessibilities while anticipating the information gap for demand size and locations. The results show the importance of flexible distribution systems during a disaster for minimizing the disaster risks.

This chapter examines the issues of the low-cost carriers (LCCs) in Japan and their impact on the domestic and international aviation markets. “Genuine” LCCs, such as Peach Aviation and Jetstar Japan, began their operations in 2012 to follow the new movement of low-cost and low-fare airlines, which are different from the “new emerging” airlines, such as Skymark and AIRDO that appeared in the late 1990s. We discuss the recent history of LCCs in Japan, the characteristics of each LCC, the competitiveness of the high-speed railway in the domestic market, the impact of open sky policies, and the contribution of inbound foreign visitors to the international passenger volume increase. As LCCs in Japan have recently begun operations, they can continue to play a significant role in the Japanese aviation market.

The purpose of this paper is to propose a model for allocating resources in various zones after a large-scale disaster. This study is motivated by the social dissatisfaction caused by inefficient relief distribution.

This study introduces an agent-based model (ABM) framework for integrating stakeholders’ interests. The proposed model uses the TOPSIS method to create a hierarchy of demand points for qualitative and quantitative parameters. A decomposition algorithm has been proposed to solve fleet allocation.

Relief distribution based on the urgency of demand points increases social benefit. A decomposition approach generates higher social benefit than the enumeration approach. The transportation cost is lower in the enumeration approach.

This study does not consider fleet contracts explicitly, but rather assumes a linear cost function for computing transportation costs.

The outcomes of this study can be a valuable tool for relief distribution planning. This model may also help reduce the social dissatisfaction caused by ad hoc relief distribution.

This study introduces an ABM for humanitarian logistics, proposes a decomposition approach, and explores the ontology of stakeholders of humanitarian logistics specific to last-mile distribution.

The purpose of this paper is to evaluate the logistics performance of intermodal freight transportation, a reasonably innovative methodology, to Thailand.

Fuzzy set techniques are applied to assess the meaning of logistics performance within the decision process of freight operators. The fuzzy‐analytical hierarchy process is applied to identify the relative significance among the attributes in the hierarchy framework levels. Consequently, the fuzzy‐multi‐criteria analysis is used to assess decision makers' perception of the logistics performance via proper assignment of numerical scores. The subjective judgments for hierarchical attributes are transformed into fuzzy degrees of score.

Results show a summary of performance indices for different levels in the hierarchy framework. The results demonstrate that the lack of coordination among modes limit the attractiveness of intermodal system. In addition, the methodology is proposed to examine changing variables regarding modal shift and challenge the truck dominance in Thailand.

The proposed framework is only a starting point for integrating the views of logistics operators in the analytical processes. This study did not include several external social costs such as accidents, congestion, and environmental costs.

The methodology provides an approach lead to the index values for assessment and comparative analysis. The strengths and limitations of each alternative were benchmarked relative to a set of hierarchical attributes. Sensitivity analyses of significant variables are performed to examine the impact on changed costs and services levels. The model can entail use of corresponding parameters to improve a logistics system.

The performance measurement is formulated from the modal choice perspective with a human decision problem. The use of logistics performance base indicators has been linked to the intermodal transport system. This study extends the newly developed methodological framework to evaluate the logistics performance of intermodal transportation.