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Low cost carriers (LCCs) have become one of the most significantly growing parts of the airline servicing market. This new player has redesigned the whole airline industry, which was previously led by the national/international full-service airline companies. Considering such advancements, the hub locations of LCCs became an important issue than ever before. Within this concept, a guiding framework is developed for an LCC company, which is in search of a new hub airport location within Turkey to satisfy the demand and attract new passengers.

An interval-valued intuitionistic fuzzy (IVIF) sets based weighted aggregated sum product assessment (WASPAS) and multi-objective optimization by ratio analysis (MULTIMOORA) methods are developed for decision-making processes.

Five airport locations are evaluated using the developed method. Results showed that in determining hub locations for LCCs, potential number of passengers of the city, airport quality and the number of hotels within the city are obtained as the three most important criteria among 12 evaluation criteria. The best location for the LCC company is determined as Antalya Airport.

To apply the proposed method to a different set of alternatives, data gathered on comparing location of alternatives from experts should be updated.

Proposed hybrid framework is presented as the first time in the literature as a decision-making tool. In order to validate framework's applicability, efficiency and effectiveness, a comparison and a sensitivity analysis are conducted at the end of the study.

The purpose of this research is to identify a province in Thailand where total transportation cost for shipping grocery goods from this province to customers in all other provinces is the lowest.

Transportation distances among provinces, freight rate and the number of population in each province were gathered. Total transportation cost was computed by taking distance, tapering freight rate and population including that in original province into account.

Based on pre-set assumptions, it reveals that Saraburi province has the lowest total transportation cost.

This research emphasizes only transportation cost. For future research, other monetary and non-monetary factors such as land, labor, investment incentive, local government regulation should be considered together.

This is an industry-based research especially for retail and fast-moving consumer goods businesses.

This practitioner paper is one of the first to identify population, freight rate and distance-based warehouse location which can be determined as a location for Thailand’s logistics hub, particularly for retail or fast-moving consumer goods business in Thailand.

The purpose of this paper is to provide an insight to the outsourcing decision-making through investigating if the old evaluation/selection criteria and methods still fit with current business priorities or not and, therefore, to identify the appropriate criteria and methods to develop a new selection framework. Since the economic recession of 2008, logistics outsourcing decisions have become more prominent to avoid high fixed costs and heavy investment requirements and to achieve competitive advantages.

This is a focused literature review prepared after analyzing 56 articles related to the logistics service provider (LSP) evaluation and selection methods and criteria during 2008-2013. The academic articles are analyzed based on research focus/area, evaluation and selection methodology/methods and evaluation and selection criteria. Then reviewed result is compared with previous literature studies for the periods (1991-2008) to identify any possible shifts.

The review reveals that: several problems in current LSPs literature have been identified; the reviewed papers can be categorized into seven groups, the usage and importance of evaluation and selection criteria fluctuate during different periods; 12 crucial criteria have been identified, increasing the importance of specific selection methods and the integrated models and fuzzy logic in logistics literature. Then, a comprehensive LSPs’ evaluation and selection framework has been developed.

To the best of our knowledge, this is the first focused logistics outsourcing study that reviews the 2008-2013 period in detail, comparing results with previous literature studies, identifies current LSPs literature problems/gaps, new trends and shifts in the way that LSPs are evaluated and selected, identifies crucial selection criteria and proposes a new holistic LSPs evaluation and selection framework. In addition, it identifies important issues for future research.

The purpose of this paper is to examine the efficacy of diversification-based learning (DBL) in expediting the performance of simulated annealing (SA) in hub location problems.

This study proposes a novel diversification-based learning simulated annealing (DBLSA) algorithm for solving p-hub median problems. It is executed on MATLAB 11.0. Experiments are conducted on CAB and AP data sets.

This study finds that in hub location models, DBLSA algorithm equipped with social learning operator outperforms the vanilla version of SA algorithm in terms of accuracy and convergence rates.

Hub location problems are relevant in aviation and telecommunication industry. This study proposes a novel application of a DBLSA algorithm to solve larger instances of hub location problems effectively in reasonable computational time.

To the best of the author’s knowledge, this is the first application of DBL in optimisation. By demonstrating its efficacy, this study steers research in the direction of learning mechanisms-based metaheuristic applications.

With the proliferation of e-commerce companies, express delivery companies must increasingly maintain the efficient expansion of their networks in accordance with growing demands and lower margins in a highly uncertain environment. This paper provides a framework for leveraging demand data to determine sustainable network expansion to fulfill the increasing needs of startups in the express delivery industry.

While the literature points out several hub assignment methods, the authors propose an alternative spherical-clustering algorithm for densely urbanized population environments to strengthen the accuracy and robustness of current models. The authors complement this approach with straightforward mathematical optimization and simulation models to generate and test designs that effectively align environmentally sustainable solutions.

To examine the effects of different degrees of demand variability, the authors analyzed this approach's performance by solving a real-world case study from an express delivery company's primary market. The authors structured a four-stage implementation framework to facilitate practitioners applying the proposed model.

Previous investigations explored driving distances on a spherical surface for facility location. The work considers densely urbanized population and traffic data to simultaneously capture demand patterns and other road dynamics. The inclusion of different population densities and sustainability data in current models is lacking; this paper bridges this gap by posing a novel framework that increases the accuracy of spherical-clustering methods.

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.

One of the practical issues in the area of location and allocation is the location of the hub. In recent years, exchange rates have fluctuated sharply for a number of reasons such as sanctions against the country. Natural disasters that have occurred in recent years caused delays in hub servicing. The purpose of this study is to develop a mathematical programming model to minimize costs, maximize social responsibility and minimize fuel consumption so that in the event of a disruption in the main hub, the flow of materials can be directed to its backup hub to prevent delays in flow between nodes and disruptions in hubs.

A multi-objective mathematical programming model is developed considering uncertainty in some parameters, especially cost as fuzzy numbers. In addition, backup hubs are selected for each primary hub to deal with disruption and natural disasters and prevent delays. Then, a robust possibilistic method is proposed to deal with uncertainty. As the hub location-allocation problem is considered as NP-Hard problems so that exact methods cannot solve them in large sizes, two metaheuristic algorithms including a non-dominated sorting genetic algorithm non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) are applied to tackle the problem.

Numerical results show the proposed model is valid. Also, they demonstrate that the NSGA-II algorithm outperforms the MOPSO algorithm.

The proposed model was implemented in one of the largest food companies in Iran, which has numerous products manufactured in different cities, to seek the hub locations. Also, due to several reasons such as road traffic and route type the difference in the rate of fuel consumption between nodes, this model helps managers and decision-makers to choose the best locations to have the least fuel consumption. Moreover, as the hub set up increases the employment rate in that city and has social benefits as it requires hiring some staff.

This paper investigates the hub location problem considering backup hubs with multiple objective functions to deal with disruption and uncertainty. Also, this study examines how non-hub nodes are assigned to hub nodes.

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.

This research presents a multiproject scheduling and resource management (MPSRM) model that includes an M/M/c/n queue system, a p-hub median model, a parallel machine scheduling and a hub location problem solution method. This research aims to design a project network and then sequence raw materials delivery to hub factories.

This research is implemented as a case study in construction and industrial company. It considers several mines to supply raw materials for production in hub factories. In the sequencing phase, a parallel mine scheduling problem specifies the delivery of raw materials to hub factories. Furthermore, a multisource project scheduling model is studied and designed for building project-oriented companies.

The results suggest that the proposed MPSRM model in this study significantly reduces project transportation costs. Therefore, creating accurate planning in projects, especially in construction projects where transportation plays an important role, can help reduce time and costs. Researchers, project managers and those dealing with projects can use this model to exploit their projects.

When the number of construction projects in a construction company increases in a region, choosing an appropriate strategy to supply resources and raw materials becomes very important in terms of profit and loss and project completion as scheduled. An increase in transportation demands alongside the economic development on the one hand and providing competitive transportation services, on the other hand, have increasingly spotlighted the significance of hub networks in transportation systems. In addition, in this research, there is no suitable access road from the mines to the project sites, and considering the workload, if any of the projects become a hub, a proper road should be built.

To the best of the knowledge, there is no outstanding research in which a p-hub median location problem by considering queuing model and different transportation modes and a parallel machine scheduling problem are studied simultaneously.