Artificial Electric Field Algorithm with Greedy State Transition Strategy for Spherical Multiple Traveling Salesmen Problem

The multiple traveling salesman problem (MTSP) is an extension of the traveling salesman problem (TSP). It is found that the MTSP problem on a three-dimensional sphere has more research value. In a spherical space, each city is located on the surface of the Earth. To solve this problem, an integer-serialized coding and decoding scheme was adopted, and artificial electric field algorithm (AEFA) was mixed with greedy strategy and state transition strategy, and an artificial electric field algorithm based on greedy state transition strategy (GSTAEFA) was proposed. Greedy state transition strategy provides state transition interference for AEFA, increases the diversity of population, and effectively improves the accuracy of the algorithm. Finally, we test the performance of GSTAEFA by optimizing examples with different numbers of cities. Experimental results show that GSTAEFA has better performance in solving SMTSP problems than other swarm intelligence algorithms.

Penerapan Bat Algorithm Dalam Penyelsaian Kasus Travelling Salesman Problem (TSP) Pada Internship Program

This optimization is an optimization case that organizes all possible and feasible solutions in discrete form. One form of combinatorial optimization that can be used as material in testing a method is the Traveling Salesman Problem (TSP). In this study, the bat algorithm will be used to find the optimum value in TSP. Utilization of the Metaheuristic Algorithm through the concept of the Bat Algorithm is able to provide optimal results in searching for the shortest distance in the case of TSP. Based on trials conducted using data on the location of student street vendors, the Bat Algortima is able to obtain the global minimum or the shortest distance when compared to the nearest neighbor method, Hungarian method, branch and bound method.

A Microlearning path recommendation approach based on ant colony optimization

This paper presents the technical proposal of a novel approach based on Ant Colony Optimization (ACO) to recommend personalized microlearning paths considering the learning needs of the learner. In this study, the information of the learner was considered from a disciplinary ICT perspective, since the characteristics of our learner correspond to those of a professor with variable characteristics, such as the level of knowledge and their learning status. The recommendation problem is approached as an instance of the Traveling Salesman Problem (TSP), the educational pills represent the cities, the paths are the relationships between educational pills, the cost of going from one pill to another can be estimated by their degree of difficulty as well as the performance of the learner during the individual test. The results prove the approach proposal capacity to suggest microlearning path personalized recommendation according to the different levels of knowledge of the learners. The higher the number of learners, the behavior of the algorithm benefits in terms of stability.

Using Fuzzy Inference to Evaluation Suppliers in Diyala General Electric Industries Company

The research aims to evaluate the suppliers at Diyala general electric industries company conducted in an environment of uncertainty and fuzzy where there is no particular system followed by the company, and also aims to use the problem of traveling salesman problem in the process of transporting raw materials from suppliers to the company in a fuzzy environment. Therefore, a system based on mathematical methods and quantity was developed to evaluate the suppliers. Fuzzy inference system (FIS) and fuzzy set theory were used to solve this problem through (Matlab) and the problem of the traveling salesman in two stages was also solved by the first stage of eliminating the fuzzing of the environment using the rank function method, while the second stage used the method of the nearest neighbor to solve the traveling salesman problem (TSP) by drawing a path that facilitates the process of transporting raw materials in the least time where the programming (Winqsb) was used. The most important thing that was reached is the mechanism of evaluating the suppliers by giving a percentage to each supplier and also their ranking where the supplier (Japanese company) got the first place and it was (87.3) ... etc. The raw materials process was used in the least time and obtained at the lowest time of the transfer, which is 292 minutes

Enhanced Self-Organizing Map Solution for the Traveling Salesman Problem

Usando um método aprimorado de Mapa Auto-Organizável, fornecemos soluções abaixo do ideal para o Problema do Caixeiro Viajante. Além disso, empregamos o ajuste de hiperparâmetros para identificar os recursos mais críticos do algoritmo. Todas as melhorias no trabalho de benchmark trouxeram resultados consistentes e podem inspirar esforços futuros para melhorar este algoritmo e aplicá-lo a diferentes problemas.

Sustainable Urban Delivery: The Learning Process of Path Costs Enhanced by Information and Communication Technologies

Today, local administrations are faced with the presence of greater constraints in terms of the use of space and time. At the same time, large amount of data is available to fleet managers that can be used for controlling their fleets. This work is set in the context defined by sustainable city logistics, and information and communication technologies (ICTs), to formalize the three themes of the smart city (transport, ICTs and energy savings) in a single problem. Following this, the main purpose of the study is to propose a unified formulation of the basic problem of fleets, i.e., the traveling salesman problem (TSP), which explicitly includes the use of emerging information and communication technologies (e-ICTs) pointing out the learning process of path costs in urban delivery. This research explores the opportunity to extend the path cost formation with a within-day and day-to-day learning process, including the specification of the attributes provided by e-ICTs. As shown through a real test case, the research answers to queries coming from operators and collectivities to improve city liveability and sustainability. It includes both economic sustainability for companies/enterprises and environmental sustainability for local administrations (and collectivities). Besides contributing to reduce the times and kms travelled by commercial vehicles, as well as the interference of freight vehicles with other traffic components, it also contributes to road accident reduction (social sustainability). Therefore, after the re-exanimation of TSP, this paper presents the proposed unitary formulation and its benefits through the discussion of results obtained in a real case study. Finally, the possible innovation guided by e-ICT is pointed out.