Uavs path planning under a bi-objective optimization framework for smart cities

Unmanned aerial vehicles (UAVs) have been used extensively for search and rescue operations, surveillance, disaster monitoring, attacking terrorists, etc. due to their growing advantages of low-cost, high maneuverability, and easy deployability. This study proposes a mixed-integer programming model under a multi-objective optimization framework to design trajectories that enable a set of UAVs to execute surveillance tasks. The first objective maximizes the cumulative probability of target detection to aim for mission planning success. The second objective ensures minimization of cumulative path length to provide a higher resource utilization goal. A two-step variable neighborhood search (VNS) algorithm is offered, which addresses the combinatorial optimization issue for determining the near-optimal sequence for cell visiting to reach the target. Numerical experiments and simulation results are evaluated in numerous benchmark instances. Results demonstrate that the proposed approach can favorably support practical deployability purposes

Consensus modeling with probability and cost constraints under uncertainty opinions

Goal programming is often applied into uncertain group decision making to achieve the optimal solution. Exiting models focus on either the minimum cost (guaranteeing negotiation budget) or the maximum utility (improving satisfaction level). This paper constructs a stochastic optimization cost consensus group decision making model adopting the minimum budget and the maximum utility as objective function simultaneously to study the negotiation consensus with decision makers' opinions expressed in the forms of multiple uncertain preferences such as utility function and normal distribution. Thus, the proposed model is a generalization of the existing cost consensus model and utility consensus model, respectively. Furthermore in this model, utility priority coefficients cause acceptable budget range and chance constraint shows the probability of reaching consensus. Differing from previous optimization models, the proposed model designs a Monte Carlo simulation combined with Genetic Algorithm to reach an optimal solution, which makes it more applicable to real-world decision making

Extending the solid step fixed-charge transportation problem to consider two-stage networks and multi-item shipments

This paper develops a new mathematical model for a capacitated solid step fixed-charge transportation problem. The problem is formulated as a two-stage transportation network and considers the option of shipping multiple items from the plants to the distribution centers (DC) and afterwards from DCs to customers. In order to tackle such an NP-hard problem, we propose two meta-heuristic algorithms; namely, Simulated Annealing (SA) and Imperialist Competitive Algorithm (ICA). Contrary to the previous studies, new neighborhood strategies maintaining the feasibility of the problem are developed. Additionally, the Taguchi method is used to tune the parameters of the algorithms. In order to validate and evaluate the performances of the model and algorithms, the results of the proposed SA and ICA are compared. The computational results show that the proposed algorithms provide relatively good solutions in a reasonable amount of time. Furthermore, the related comparison reveals that the ICA generates superior solutions compared to the ones obtained by the SA algorithm

Neutrosophic Multi-Criteria Decision Making

The notion of a neutrosophic quadruple BCK/BCI-number is considered in the first article (“Neutrosophic Quadruple BCK/BCI-Algebras”, by Young Bae Jun, Seok-Zun Song, Florentin Smarandache, and Hashem Bordbar), and a neutrosophic quadruple BCK/BCI-algebra, which consists of neutrosophic quadruple BCK/BCI-numbers, is constructed. Several properties are investigated, and a (positive implicative) ideal in a neutrosophic quadruple BCK-algebra and a closed ideal in a neutrosophic quadruple BCI-algebra are studied. Given subsets A and B of a BCK/BCI-algebra, the set NQ(A,B), which consists of neutrosophic quadruple BCK/BCInumbers with a condition, is established. Conditions for the set NQ(A,B) to be a (positive implicative) ideal of a neutrosophic quadruple BCK-algebra are provided, and conditions for the set NQ(A,B) to be a (closed) ideal of a neutrosophic quadruple BCI-algebra are given. Techniques for the order of preference by similarity to ideal solution (TOPSIS) and elimination and choice translating reality (ELECTRE) are widely used methods to solve multicriteria decision-making problems. In the second research article (“Decision-Making with Bipolar Neutrosophic TOPSIS and Bipolar Neutrosophic ELECTRE-I”), Muhammad Akram, Shumaiza, and Florentin Smarandache present the bipolar neutrosophic TOPSIS method and the bipolar neutrosophic ELECTRE-I method to solve such problems. The authors use the revised closeness degree to rank the alternatives in the bipolar neutrosophic TOPSIS method. The researchers describe the bipolar neutrosophic TOPSIS method and the bipolar neutrosophic ELECTRE-I method by flow charts, also solving numerical examples by the proposed methods and providing a comparison of these methods. In the third article (“Interval Neutrosophic Sets with Applications in BCK/BCI-Algebra”, by Young Bae Jun, Seon Jeong Kim and Florentin Smarandache), the notion of (T(i,j),I(k,l),F(m,n))-interval neutrosophic subalgebra in BCK/BCI-algebra is introduced for i,j,k,l,m,n infoNumber 1,2,3,4, and properties and relations are investigated. The notion of interval neutrosophic length of an interval neutrosophic set is also introduced, and the related properties are investigated

Advances in Public Transport Platform for the Development of Sustainability Cities

Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency