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Martian outpost : the challenges of establishing a human settlement on Mars
From the Publisher: Martian Outpost provides a unique and detailed insight into the various enabling technologies, mission architectures, medical requirements, and training needed to send humans to Mars. It focuses on the mission objectives and benefits, and the risks and complexities which are compounded when linked to an overall planet exploration program involving a permanent presence on the surface.
Book
Ant Colony Optimization (ACO) Algorithm for Determining The Nearest Route Search in Distribution of Light Food Production
At this time the development of technology that forces everything must move fast, the efficiency of time becomes a measure of the success of a distribution or production. the continuity of production and the success of production itself is related to distribution. When the distribution fails, production will fail. Indonesian people especially in North Sumatra often consume snacks when free time and snacks are the most consumed food by the Indonesian population until now the production of snacks in Indonesia rose to 50% in 2019, causing the food production to have a concept in timely distribution without experiencing delays in distributing goods that have been produced. One of the expeditions in Indonesia experienced problems in terms of late distribution of goods up to 15-20%, this would have a bad impact on the industry in the future, so to overcome the problems above the application of the ant colony optimization algorithm can help the above problems by placing 4 ants and the ants will spread from point A to point H. In the results of this study, there are 4 ants that move together where the best results are obtained by ant 2, closest to the point H, where the value obtained reaches 0,00015
Journal Article
Settler society in the Australian colonies : self-government and imperial culture
Examines the rising numbers of free settlers from the 1820s to the 1860s, their dependence on Aboriginal, immigrant, and convict under-paid laborers, and the slow development of representative government.
Book
A novel collaborative optimization algorithm in solving complex optimization problems
To overcome the deficiencies of weak local search ability in genetic algorithms (GA) and slow global convergence speed in ant colony optimization (ACO) algorithm in solving complex optimization problems, the chaotic optimization method, multi-population collaborative strategy and adaptive control parameters are introduced into the GA and ACO algorithm to propose a genetic and ant colony adaptive collaborative optimization (MGACACO) algorithm for solving complex optimization problems. The proposed MGACACO algorithm makes use of the exploration capability of GA and stochastic capability of ACO algorithm. In the proposed MGACACO algorithm, the multi-population strategy is used to realize the information exchange and cooperation among the various populations. The chaotic optimization method is used to overcome long search time, avoid falling into the local extremum and improve the search accuracy. The adaptive control parameters is used to make relatively uniform pheromone distribution, effectively solve the contradiction between expanding search and finding optimal solution. The collaborative strategy is used to dynamically balance the global ability and local search ability, and improve the convergence speed. Finally, various scale TSP are selected to verify the effectiveness of the proposed MGACACO algorithm. The experiment results show that the proposed MGACACO algorithm can avoid falling into the local extremum, and takes on better search precision and faster convergence speed.
Journal Article
Preventive maintenance scheduling optimization based on opportunistic production-maintenance synchronization
Equipment maintenance is momentous for improving production efficiency, how to integrate maintenance into production to address uncertain problems has attracted considerable attention. This paper addresses a novel approach for integrating preventive maintenance (PM) into production planning of a complex manufacturing system based on availability and cost. The proposed approach relies on two phases: firstly, this study predicts required capacity of each machine through extreme learning machine algorithm. Based on analyzing historical data, the opportunistic periods are calculated for implementing PM tasks to have less impact on production and obtain the PM interval and duration. Secondly, this study obtains the scheduling planning and the least number of maintenance personnel through an improved ant colony optimization algorithm. Finally, the feasibility and benefits of this approach are investigated based on empirical study by using historical data from real manufacturing execution system and equipment maintenance system. Experimental results demonstrate the effectiveness of proposed approach, reduce personnel number while guarantee the maintenance tasks. Therefore, the proposed approach is beneficial to improve the company’s production efficiency.
Journal Article
The 1857 Indian Uprising and the British Empire
Situating the 1857 Indian uprising within an imperial context, Jill C. Bender traces its ramifications across the four different colonial sites of Ireland, New Zealand, Jamaica, and southern Africa. Bender argues that the 1857 uprising shaped colonial Britons' perceptions of their own empire, revealing the possibilities of an integrated empire that could provide the resources to generate and 'justify' British power. In response to the uprising, Britons throughout the Empire debated colonial responsibility, methods of counter-insurrection, military recruiting practices, and colonial governance. Even after the rebellion had been suppressed, the violence of 1857 continued to have a lasting effect. The fears generated by the uprising transformed how the British understood their relationship with the 'colonized' and shaped their own expectations of themselves as 'colonizer'. Placing the 1857 Indian uprising within an imperial context reminds us that British power was neither natural nor inevitable, but had to be constructed.
Book
Integrated process planning and scheduling: an enhanced ant colony optimization heuristic with parameter tuning
This study develops an enhanced ant colony optimization (E-ACO) meta-heuristic to accomplish the integrated process planning and scheduling (IPPS) problem in the job-shop environment. The IPPS problem is represented by AND/OR graphs to implement the search-based algorithm, which aims at obtaining effective and near-optimal solutions in terms of makespan, job flow time and computation time taken. In accordance with the characteristics of the IPPS problem, the mechanism of ACO algorithm has been enhanced with several modifications, including quantification of convergence level, introduction of node-based pheromone, earliest finishing time-based strategy of determining the heuristic desirability, and oriented elitist pheromone deposit strategy. Using test cases with comprehensive consideration of manufacturing flexibilities, experiments are conducted to evaluate the approach, and to study the effects of algorithm parameters, with a general guideline for ACO parameter tuning for IPPS problems provided. The results show that with the specific modifications made on ACO algorithm, it is able to generate encouraging performance which outperforms many other meta-heuristics.
Journal Article
The cultural legacy of German colonial rule
\"This edited volume explores social, economic, political, and cultural practices generated by African, Asian, and Oceanic individuals and groups within the context and aftermath of German colonialism. The volume contributes to current debates on transnational and intercultural processes while highlighting the ways in which the colonial period is embedded in larger processes of globalization.\"-- Details from publisher.
Book
Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints
This paper focuses on minimizing the makespan for a reentrant hybrid flow shop scheduling problem with time window constraints (RHFSTW), which is often found in manufacturing systems producing the slider part of hard-disk drive products, in which production needs to be monitored to ensure high quality. For this reason, production time control is required from the starting-time-window stage to the ending-time-window stage. Because of the complexity of the RHFSTW problem, in this paper, genetic algorithm hybridized ant colony optimization (GACO) is proposed to be used as a support tool for scheduling. The results show that the GACO can solve problems optimally with reasonable computational effort.
Journal Article