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The meaning of sustainability is very broad and has many pillars such as the economy, environment and society. In the tourism industry, another important pillar is security. Tourism security affects the satisfaction and pleasure of tourists on a trivial level, and life and injuries on a significant level. Thus, unless security is guaranteed, tourists will not be able to fully enjoy the attractions and will not even consider the travel itself. Such tourist behavior has a significant impact on short-term and long-term tourism sustainability. Therefore, to enhance tourism security, many policies and frameworks have been suggested and announced in recent years. However, without efficient guidelines for the installation and operation of security devices, it may be hard to obtain actual effectiveness. To support real implementation of security systems in the tourism industry, this study quantitatively addresses the installation and operation issue of security devices in an optimal manner. A complementary cooperation of Closed-Circuit Television (CCTV) and Unmanned Aerial Vehicles (UAV) is suggested to efficiently monitor the key locations of tourism destinations and improve the security. Two mathematical models are developed to derive the optimal location of CCTVs, and the optimal operation schedule of UAVs over multiple time periods. Security requirements, service range, and budget are considered as realistic constraints. The validity of the models is demonstrated through a realistic case study of Nice, France.

Unmanned aerial vehicles (UAVs) are expected to make groundbreaking changes in the logistics industry. Leading logistics companies have been developing and testing their usage of UAVs recently as an environmentally friendly and cost-effective option. In this paper, we investigate how much the UAV delivery service is environmentally friendly compared to the traditional ground vehicle (GV) delivery service. Since there are fuel (battery) and loadable weight restrictions in the UAV delivery, multi-hopping of UAV is necessary, which may cause a large consumption of electrical energy. We present a two-phase approach. In Phase I, a new vehicle routing model to obtain optimal delivery schedules for both UAV-alone and GV-alone delivery systems is proposed, which considers each system&rsquo, s restrictions, such as the max loadable weight and fuel replenishment. In Phase II, CO2 emissions are computed as a sustainability measure based on the travelling distance of the optimal route obtained from Phase I, along with various GV travel-speeds. A case study finds that the UAV-alone delivery system is much more CO2 efficient in all ranges of the GV speeds investigated.

The platooning of autonomous smart vehicles in a high-speed driving environment is a technology that can be achieved in the near future, and some similar driving-assistive technologies have already been put in practice. There are a variety of advantages to platooning, and one of them is the environmental aspect. This study endeavored to perform a mathematical analysis of the environmental aspect of forming a platoon of smart vehicles. For that, a mathematical experiment was designed with four kinds of scenarios, and each scenario had a different operation profile in terms of the velocity and acceleration of each smart vehicle. The power consumption and both forming distance and time were derived variously according to each scenario through mathematical experiments, and it was observed that the length of the acceleration period and the average operation velocity of the smart vehicles had a significant impact on the environmental effect of platoon formation. It is hoped that this study will be a touchstone for various kinds of platooning algorithm research considering the environment.

In the green manufacturing system that pursues the reuse of used products, the residual value of collected used products (CUP) hugely affects a variety of managerial decisions to construct profitable and environmental remanufacturing plans. This paper deals with a closed-loop green manufacturing system for companies which perform both manufacturing with raw materials and remanufacturing with collected used products (CUP). The amount of CUP is assumed as a function of buy-back cost while the quality level of CUP, which means the residual value, follows a known distribution. In addition, the remanufacturing cost can differ according to the quality of the CUP. Moreover, nowadays companies are subject to existing environment-related laws such as Extended Producer Responsibility (EPR). Therefore, a company should collect more used products than its obligatory take-back quota or face fines from the government for not meeting its quota. Through the development of mathematical models, two kinds of inspection policies are examined to validate the efficiency of two different operation processes. To find a managerial solution, a genetic algorithm is proposed and tested with numerical examples.