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Most often mobile robots are required to move and work in environments containing potential sources of danger, such as fire in rescue operations, landmines and fighters in battlefields, etc. In order to successfully complete an assigned task, a robot must evade the aforementioned danger sources. A multi-objective path planning algorithm based on Dynamic Neighborhood Particle Swarm Optimization for...
This paper presents the methodology and its correspondent software conceived by Daimon Engineering to propose the medium voltage distribution system work plan of CELESC. To accomplish this job, a specially designed computer program has been created to take into account several technical variables, according to the type of problem (overcapacity of conductors and voltage drops). As a result of this...
This paper deals with proposing an inspection plan framework for serial manufacturing system with multiple objectives. The proposed framework supports decision making during Monitoring Inspection (MI) and Conformity Inspection (CI) design. It provides a multi-objective mathematical model to find the optimal inspection plan by considering the location, the type of inspection (MI and CI) and the frequency...
We present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi Access Points (APs) and Long Term Evolution (LTE) femtocells. We propose a design framework based on Multi-objective Biogeography-based Optimization (MOBBO)...
This paper presents the recent developments of an Optimal Path Planning — Decision Support System (OPP-DSS). The designed framework is based on multi-objective optimization algorithms providing a set of Pareto efficient solutions representing a trade-off among mission objectives. Meteorological and Oceanographic (METOC) and Automatic Identification System (AIS) vessel traffic data are integrated and...
Aggregate planning refers to the determination of production, inventory and capacity levels for a medium term. Traditionally standard mathematical programming formulation is used to devise the aggregate plan so as to minimize the total cost of operations. However, this formulation is purely an economic model that does not include sustainability considerations. In this study, we revise the standard...
As an important part of the new energy industry, electric vehicle (EV) is attracting widespread attention all around the world. To make the EV charge-swap stations meet the growing demand for charge-swap service, this paper proposes a multi-objective optimization model, considering the investment of the service providers and the service capacity. Besides, a case study, based on a certain city's real...
This paper presents the novel access network planning model for Wireless Interoperability for Microwave Access. The proposed model aims to assign optimize amount and location of Base Stations in study area. Integer Linear Programming is used for formulating optimization problem which objectives are minimize installation cost and maximize service coverage simultaneously. Numerical network planning...
Next Release Problem (NRP) is a complex combinatorial optimization problem consisting of identifying a subset of software requirements maximizing the business value under given constraints such as cost and resource limitation, time and functionality related dependencies between requirements. NRP can be mathematically formulated as an integer linear programming problem and previous researches solve...
Frequent occurrences of meteorological disasters (MD) in recent years have revealed the deficiencies of traditional transmission network planning (TNP) methods, which fail to establish mathematical relationship between the MD and the transmission line outage rate (TLOR) when calculating the vulnerability index of transmission network. As a result, the planning schemes are usually unable to determine...
In this paper, a novel hybrid genetic algorithm is presented for optimization in radiation therapy treatment planning. The proposed Reduced Order Memetic Algorithm (ROMA) is a combination of an evolutionary multi-objective optimization algorithm and gradient-based local search in a reduced order space. The gradient-based optimizer is used for a fast local search and is a variant of the sequential...
There are many multi-objective planning problems in emergency decision-making domain. HTN planners were widely used in emergency decision-making, while they have limited ability to solve optimization, especially multi-objective optimization. Aimed to handling multi-objective in HTN planners, this paper proposes a novel method based on SHOP2, which is a domain-independent state-based forward HTN planner...
Preventive maintenance (PM) plays a very important role in production process. In this paper, the optimization PM planning in finite time horizon for a single machine with minimal repair at failures is discussed. Not only two conflicting objectives of maintenance cost and maintenance time but also two constraints of the reliability and availability of the machine are simultaneously considered in the...
Optimizing the Quality-of-Service (QoS) levels of a service workflow is essential for the user satisfaction in Service-oriented Computing. For that purpose, QoS computation models are applied to reflect the actual QoS experienced by the user during service execution. Current QoS models ignore the possible dependencies of QoS attributes, such as the dependency on the time of the execution or on the...
The rise of distributed generation (DG) and the development of smart grid call attention to the research on the interconnection of distributed generation. The research of optimal allocation of distributed generation in smart grid is taken. A multi-objective optimization model is proposed that takes account into economic benefits and environmental benefits. The network loss sensitivity analysis is...
In order to solve the conflicting objectives in power network planning, various evolutionary methods to multi-objective optimization have been developed, however, some studies of different methods are often restricted to the quantitatively and the approaches of Pareto front. In this paper the potential and effectiveness of Pareto front-based improved quantum particle swarm algorithm (IQPSO) for solving...
With the development of national economy and the improving people's living standards, the supply capacity of distribution network, power quality and reliability requirements are increasing, the power company is facing many new challenges, one important issue is how to improve the quality and reliability of power supply at the same time, as much as possible to reduce operating, maintenance and construction...
The main objective of transmission expansion planning in deregulated power systems is to provide a non-discriminatory competitive environment for all stakeholders, while maintaining power system reliability. In this paper, a static transmission expansion methodology is proposed using a multi-objective optimization framework that is able to handle different incommensurable objectives with conflicting...
BIW modal optimization with traditional FEM method was inefficiency and usually with much mass increase. FEM analysis combined with Multi-objective Optimization method was used to improve the first order frequency of BIW. Mathematic model was built by response surface method to replace FEM model and NSGA-II was used to get non-dominated solutions. During the optimization plates with high relative...
The electrical sector has become highly competitive introducing new levels of uncertainty. In response to this situation, assessment methods and investment projects need to evolve in order to incorporate different uncertainties in the planning process and to consider adequately the multiple objectives of a competitive environment. This paper discusses an analysis method which possesses the above mentioned...
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