Solution of Travelling Salesman Problem based on Metaheuristic Techniques

The traveling salesman problem is a classic problem in combinatorial optimization. This problem is to find the shortest path that a salesman should take to traverse through a list of cities and return to the origin city. The list of cities and the distance between each pair are provided. It is an NP-complete problem i.e., class of computational problem for which no efficient solution algorithm has been found, presently there is no polynomial solution available. In this paper, we try to solve this very hard problem using various heuristics such as Simulated Annealing, Genetic Algorithm to find a near-optimal solu-tion as fast as possible. We try to escape the local optimum, using these advanced heu-ristic techniques

Non-Deterministic and Polynomial Time Problem Simulator

The Non-Deterministic and Polynomial Time Problem is a problem in combinatorial op-timization. Finding the quickest route for an object to travel through a list of cities and return to the starting city is the goal of this problem. Cities are listed, along with the dis-tance between each pair. It belongs to the category of computer problems known as NP-complete problems, for which no effective algorithmic solution has yet been discov-ered; at this time, there is no polynomial solution. In order to discover a near-optimal solution as quickly as possible, we attempted to tackle this extremely challenging prob-lem in this study utilizing a variety of heuristics, including Simulated Annealing and Ge-netic Algorithm. Using these sophisticated heuristic techniques, we at-tempt to depart from the local optimum

Modelo de otimização do espaço livre de armazenagem num silo de cereais

Este trabalho baseia-se num caso de estudo real de planeamento de operações de armazenagem num silo rural de cereais, e enquadra-se nos problemas de planeamento e programação de armazéns. Os programadores deparam-se diariamente com o problema de arranjar a melhor solução de transferência entre células de armazenagem, tentando maximizar o número de células vazias, por forma a ter maior capacidade para receber novos lotes, respeitando as restrições de receção e expedição, e as restrições de capacidade das linhas de transporte. Foi desenvolvido um modelo matemático de programação linear inteira mista e uma aplicação em Excel, com recurso ao VBA, para a sua implementação. Esta implementação abrangeu todo o processo relativo à atividade em causa, isto é, vai desde a recolha de dados, seu tratamento e análise, até à solução final de distribuição dos vários produtos pelas várias células. Os resultados obtidos mostram que o modelo otimiza o número de células vazias, tendo em conta os produtos que estão armazenados mais os que estão para ser rececionados e expedidos, em tempo computacional inferior a 60 segundos, constituindo, assim, uma importante mais valia para a empresa em causa.This work is based on a real case study for planning storage operations in a rural grain silo, and fits the problems of planning and programming of warehouses. Programmers are faced daily with the problem of finding the best solution for transfers between storage cells, trying to maximize the number of empty cells in order to have greater capacity to receive new lots, subject to receiving, dispatching, and transportation lines capacity constraints. We developed a mixed integer linear programming model and an Excel/VBA application for its implementation. This implementation included the entire process, ranging from data collection, its treatment and analysis to the final solution for the distribution of various products by various cells. The results show that the model optimizes the number of empty cells, in computation time less than 60 seconds, and thereby constitutes a significant added value to the company concerned

Drone-based delivery of clinical specimens in a rural enviroment : a feasibility study

A dissertation submitted in fulfilment of the requirements for the degree of Master of Science in Engineering by Research in the Faculty of Engineering and the Built Environment School of Electrical and Information Engineering , Private Bag 3, 2050, Johannesburg, South AfricaA framework is developed for the implementation of an autonomous drone-based delivery system. The concept stems from the need for more efficient methods of clinical transport in underdeveloped regions. A case study of a region in Mpumalanga investigates the requirements of the delivery system and scale of the intended solution. The travelling salesman problem (TSP) is used to determine that a region with 19 request points can be serviced by a single drone with a 30 minute flight range and 2 - 4 kg payload capacity. A notional region containing 20 clinics and one laboratory is used to simulate scenarios with dynamic request points using a reward-based inspection algorithm. Delivery routes are optimised based on global conditions. An evaluation of the inspection algorithm resulted in the drones averaging 103.53 km in 139.21 minutes. A framework is thus developed which allows for a theoretical scenario analysis for future implementations. The specimen turnaround time from clinic to laboratory is assessed using 120 scenarios of varying wind speed and request generation rates. In wind conditions similar to that observed in Mpumalanga (5 - 25 km/h), the drone averaged 93.94 minutes per request. At a request rate of two requests per hour the drone delivered an average of 180 samples generated in the first nine hours of simulation. At a request rate of one request every 6 hours the drone averaged 29 samples. Future work could include an in depth study of seasonal request rates and weather pattern data in order to influence the path of the drone for a further optimised approach as well as the development of more advanced optimisation algorithms.GR201

Performance Analysis For Wireless G (IEEE 802.11 G) And Wireless N (IEEE 802.11 N) In Outdoor Environment

This paper described an analysis the different capabilities and limitation of both IEEE technologies that has been utilized for data transmission directed to mobile device. In this work, we have compared an IEEE 802.11/g/n outdoor environment to know what technology is better. the comparison consider on coverage area (mobility), through put and measuring the interferences. The work presented here is to help the researchers to select the best technology depending of their deploying case, and investigate the best variant for outdoor. The tool used is Iperf software which is to measure the data transmission performance of IEEE 802.11n and IEEE 802.11g

Performance analysis for wireless G (IEEE 802.11G) and wireless N (IEEE 802.11N) in outdoor environment

This paper described an analysis the different capabilities and limitation of both IEEE technologies that has been utilized for data transmission directed to mobile device. In this work, we have compared an IEEE 802.11/g/n outdoor environment to know what technology is better. The comparison consider on coverage area (mobility), throughput and measuring the interferences. The work presented here is to help the researchers to select the best technology depending of their deploying case, and investigate the best variant for outdoor. The tool used is Iperf software which is to measure the data transmission performance of IEEE 802.11n and IEEE 802.11g