TWO PHASE HEURISTIC ALGORITHM (TPHA) PADA MULTIPLE TRAVELLING SALESMAN PROBLEM (MTSP) DAN IMPLEMENTASI PROGRAMNYA

Multiple Traveling Salesman Problem (MTSP) is one variant of Traveling Salesman Problem (TSP) which involves several salesmen in making a trip to visit several customers. In this article, the Two-Phase Heuristic Algorithm (TPHA) is used to solve MTSP problems. The algorithm classifies customers into several regions using the K-Means algorithm, which will then find a route solution for each region using a genetic algorithm. The MTSP problems that were resolved using TPHA were implemented into the Borland Delphi 7.0 programming language. Application testing was conducted using 21, 32, and 46 point cases

Homogeneous Agent Behaviours for the Multi-Agent Simultaneous Searching and Routing Problem

Through the use of autonomy Unmanned Aerial Vehicles (UAVs) can be used to solve a range of of multi-agent problems that exist in the real world, for example search and rescue or surveillance. Within these scenarios the global objective might often be better achieved if aspects of the problem can be optimally shared amongst its agents. However, in uncertain, dynamic and often partially observable environments centralised global-optimisation techniques are not achievable. Instead, agents may have to act on their own belief of the world, making the best decisions independently and potentially myopically. With multiple agents acting in a decentralised manner how can we discourage competitive behaviour and instead facilitate cooperation. This paper focuses on the specific problem of multiple UAVs simultaneously searching for tasks in an environment whilst efficiently routing between them and ultimately visiting them. This paper is motivated by this idea that collaboration can be simple and achieved without the need for a dialogue but instead through the design of the individual agent’s behaviour. By focusing on what is communicated we expand the use of a single agent behaviour. Which through minor modifications can produce distinct agents demonstrating independent, collaborative and competitive behaviour. In particular by investigating the role of sensor and communication ranges this paper will show that increased sensor ranges can be detrimental to system performance, and instead the simple modelling of nearby agents’ intent is a far better approach

Algorithms for forward and backward planning

Práce se zabývá plánováním výroby. Obsahuje teoretický popis metod používaných pro plánování a optimalizaci výroby. Popisuje problematiku úzkých míst ve výrobě. Nabízí přehled způsobů jejich identifikace a analýzu jejich vlivů na efektivitu výrobního procesu. Navrhuje odstranění úzkých míst s využitím různých druhů algoritmů. Teoretické poznatky z oblasti optimalizace a teorie grafů aplikuje při vytvoření programu určeného k minimalizaci zpoždění zakázek a doby přeseřízení strojů. Program implementuje genetický algoritmus.The thesis deals with production planning. It contains theoretical description of methods used for production planning and optimizing. Thesis describes bottleneck problems in production. It offers overview of ways to identify and analyze bottleneck influence to manufacturing process efficiency. Thesis proposes ways to eliminate bottlenecks using various algorithm types. It applies theoretical knowledges from optimization and graph theory to program creation that is focused on order delay and readjustment time minimizing. The program implements genetic algorithm.

Determinação de rotas para um navio de investigação utilizado em campanhas de pesca

Tese de mestrado em Estatística e Investigação Operacional, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, em 2018O problema de determinação de rotas para navios de investigação para campanhas de pesca, designado como Ship Routing Optimization Problem (SROP), é um problema que até agora não foi muito estudado e explorado. No problema são conhecidos o conjunto de estações de pesca a ser visitadas, o número de circuitos a determinar e o número de dias que no máximo deve durar cada circuito. Também são conhecidas as janelas temporais associadas às visitas às estações que determinam as horas de visita para cada dia e as janelas temporais associadas às visitas aos portos, que garantem que estes sejam visitados com a periodicidade previamente definida. Cada circuito deve começar e terminar no porto origem. Dadas as localizações geográficas das estações de pesca e dos portos, o objetivo do problema é minimizar a distância total percorrida e a duração total de cada circuito, garantindo que todas as estações são visitadas e respeitando as restrições das janelas temporais. Nesta dissertação, apresentam-se três modelos matemáticos em programação linear inteira mista (PLIM) para resolver o problema. Para além dos modelos, sugerem-se também heurísticas que têm como objetivo obter soluções inteiras admissíveis utilizando os modelos propostos e um solver genérico. Pretende-se comparar as três formulações a nível da qualidade dos limites inferiores para o valor ótimo, fornecidos por relaxações lineares totais e parciais e do tempo computacional gasto para obter os mesmos. Através das heurísticas pretende-se obter soluções admissíveis para todas as instâncias e os limites superiores para o valor ótimo associados aos respetivos valores. As instâncias utilizadas são baseadas em campanhas realizadas pelo IPMA (Instituto Português do Mar e da Atmosfera) para estimar a abundância e observar a distribuição geográfica de várias espécies marinhas da costa portuguesa e instâncias disponibilizadas na literatura para o Problema do Caixeiro Viajante com Seleção de Hotéis. Os resultados obtidos confirmam a complexidade do problema e a dificuldade em resolve-lo usando um solver genérico, tendo existido instâncias para as quais não foi possível encontrar uma solução admissível.The problem of determining routes for vessels in fisheries research, called the Ship Routing Optimization Problem (SROP), has not been much studied and explored. The set of fishing stations to be visited, the number of circuits to establish and the maximum number of days that each circuit should last are known, as well as the time windows associated with station visits which determine the visiting hours for each day and the windows associated with visits to the seaports assuring a predefined periodicity. Each circuit must start and end at the home seaport. Given the geographical locations of the fishing stations and seaports, the objective is to minimize the total traveled distance and the total duration of each circuit, ensuring that all stations are visited and time windows constraints are satisfied. In this dissertation, three mixed integer linear programming mathematical models are presented for the problem. Furthermore, heuristics that aim to obtain feasible integer solutions using the proposed models and a generic solver are suggested . It is intended to compare the three models in what concerns the quality of the lower bounds for the optimal value provided by partial or total linear programming relaxations and the computational time spent to obtain them. By using the heuristics, it is intended to obtain feasible solutions that provide upper bounds for all instances. The instances used are based in the campaigns realized by IPMA (Portuguese Sea and Atmosphere Institute) to estimate the abundance and observe the geographical distribution of several demersal fish species from the Portuguese continental coast and instances available in literature for the Traveling Salesman Problem with Hotel Selection. The results obtained confirm the complexity of the problem and the difficulty to solve it using a generic solver. There have been instances for which it was not possible to obtain a feasible solution

Essays on Shipment Consolidation Scheduling and Decision Making in the Context of Flexible Demand

This dissertation contains three essays related to shipment consolidation scheduling and decision making in the presence of flexible demand. The first essay is presented in Section 1. This essay introduces a new mathematical model for shipment consolidation scheduling for a two-echelon supply chain. The problem addresses shipment coordination and consolidation decisions that are made by a manufacturer who provides inventory replenishments to multiple downstream distribution centers. Unlike previous studies, the consolidation activities in this problem are not restricted to specific policies such as aggregation of shipments at regular times or consolidating when a predetermined quantity has accumulated. Rather, we consider the construction of a detailed shipment consolidation schedule over a planning horizon. We develop a mixed-integer quadratic optimization model to identify the shipment consolidation schedule that minimizes total cost. A genetic algorithm is developed to handle large problem instances. The other two essays explore the concept of flexible demand. In Section 2, we introduce a new variant of the vehicle routing problem (VRP): the vehicle routing problem with flexible repeat visits (VRP-FRV). This problem considers a set of customers at certain locations with certain maximum inter-visit time requirements. However, they are flexible in their visit times. The VRP-FRV has several real-world applications. One scenario is that of caretakers who provide service to elderly people at home. Each caretaker is assigned a number of elderly people to visit one or more times per day. Elderly people differ in their requirements and the minimum frequency at which they need to be visited every day. The VRP-FRV can also be imagined as a police patrol routing problem where the customers are various locations in the city that require frequent observations. Such locations could include known high-crime areas, high-profile residences, and/or safe houses. We develop a math model to minimize the total number of vehicles needed to cover the customer demands and determine the optimal customer visit schedules and vehicle routes. A heuristic method is developed to handle large problem instances. In the third study, presented in Section 3, we consider a single-item cyclic coordinated order fulfillment problem with batch supplies and flexible demands. The system in this study consists of multiple suppliers who each deliver a single item to a central node from which multiple demanders are then replenished. Importantly, demand is flexible and is a control action that the decision maker applies to optimize the system. The objective is to minimize total system cost subject to several operational constraints. The decisions include the timing and sizes of batches delivered by the suppliers to the central node and the timing and amounts by which demanders are replenished. We develop an integer programing model, provide several theoretical insights related to the model, and solve the math model for different problem sizes

Rapid prototyping of distributed systems of electronic control units in vehicles

Existing vehicle electronics design is largely divided by feature, with integration taking place at a late stage. This leads to a number of drawbacks, including longer development time and increased cost, both of which this research overcomes by considering the system as a whole and, in particular, generating an executable model to permit testing. To generate such a model, a number of inputs needed to be made available. These include a structural description of the vehicle electronics, functional descriptions of both the electronic control units and the communications buses, the application code that implements the feature and software patterns to implement the low-level interfaces to sensors and actuators. [Continues.