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In recent decade, reliability has been an important factor which may affect the performance of the system. In order to enhance the system reliability, redundancy allocation problem (RAP) is becoming an increasingly important tool in the stages of planning, designing, and controlling of systems. Moreover, the multi-level redundancy allocation problem (MRAP) and multiple multi-level redundancy allocation...
The disaster emergency relief plays a vital role in reducing casualties and economic losses. Emergency logistics scheduling (ELS) aims at dispatching emergency resources to the victims of disasters, which is an important event of disaster relief. In this paper, a model for ELS in disaster relief is built that includes several suppliers with a variety of resources, several kinds of vehicles, and multiple...
Although there exist numerous literatures on facility layout in manufacturing systems, studies on department layout in hospitals are relatively scarce. In this paper, we proposed a MOEA/D based approach for a hospital department layout problem, where three objectives are simultaneously optimized, namely patient flow cost, the closeness of departments and rearrangement cost. A constraint handling technology...
The Robust Vehicle Routing Problem with Time Windows has been gaining popularity over the past few years due to its focus on tackling uncertainty inherent to real world problems. Most of the current approaches in generating robust solutions require prior knowledge on the uncertainties, such as uncertainties in travel time. Hence, they are less than favorable to use in the absence of data, i.e., in...
Cognitive radio is a new network technology developed in recent years, which focuses on the low utility of spectrum in the wireless communication system. This paper proposes a new algorithm based on the immune clone optimization for unconstrained multi-objective resource allocation in the downlink OFDMA network. We first convert the constraint of data transmission rate proportionality of each user...
Evolutionary computation is a field characterized by large data sets produced either through user-driven or automatic evaluation. Because of the sheer magnitude of evolved solutions that need to be reviewed and analyzed, it can be difficult to fully utilize evolutionary data effectively. To address this challenge we present evoVersion, a system capable of applying version control methodologies to...
The recent rapid expansion of Cloud computing facilities triggers an attendant challenge to facility providers and users for methods for optimal placement of workflows on distributed resources, under the often-contradictory impulses of minimizing makespan, energy consumption, and other metrics. Evolutionary Optimization techniques that from theoretical principles are guaranteed to provide globally...
This contribution addresses the question if and how the impact of parallelization can influence the performance of an evolutionary algorithm on constrained mixed-integer nonlinear optimization problems. On a set of 200 MINLP benchmarks the performance of the MIDACO solver is numerically assessed with gradually increasing parallelization factor from 1 to 100. The results demonstrate that the efficiency...
This paper describes an approach for controlling light illuminance using the CUDA-based Self-adaptive Subpopulation Model of Genetic Programming (cuSASGP). The method involves the evolution of a genetic programming lighting control rule for the ceiling lights in an office room to satisfy different brightness requirements at each desk and reduce electric power consumption. Although the lighting control...
This paper proposes a 3D modeling system that uses multi-player interactive genetic algorithm (MiGA) to simplify the 3D modeling process for ordinary persons who wish to model pairs of glasses. The proposed system has three advantages: First, users are able to create 3D models via simple operations such as evaluation of 3D models. Second, this system reduces user fatigue by showing the information...
In this paper, the effect of the population size on the performance of the MAX-MIN ant system for dynamic optimization problems (DOPs) is investigated. DOPs are generated with the dynamic benchmark generator for permutation-encoded problems. In particular, the empirical study investigates: a) possible dependencies of the population size parameter with the dynamic properties of DOPs; b) the effect...
Multi-objective optimization problems with interval (MOPs-I) uncertainties parameters are common in practice. Evolutionary multi-objective (EMO) algorithms are popularly employed to solve these problems due to their powerful explorations. The comparison strategies among interval objectives of MOPs-I are crucially important for obtaining a superior Pareto front when applying EMOs. By effectively combining...
This paper addresses the solution of optimal control problems with multiple and possibly conflicting objective functions. The solution strategy is based on the integration of Direct Finite Elements in Time (DFET) transcription into the Multi Agent Collaborative Search (MACS) framework. Multi Agent Collaborative Search is a memetic algorithm in which a population of agents performs a set of individual...
During orbital operations of the space station, several test missions require astronauts to conduct extravehicular activities. Because of the limitations of man-hours and resources such as extravehicular spacesuits, the overall programming of spacewalk events is a critical issue to address in operation mission planning for the space station. Based on the theory of bin packing, this paper establishes...
In this paper we explore uncertainty quantification and management in an industrial context. We use a multielement airfoil section at take-off conditions, the so called Airbus Test Case A, for the demonstration of our methods. We also try to identify through this case study the elements that are necessary to synthesise in order to move towards the characterisation of multi-disciplinary complexities...
Optimal control of aircraft descent is important to efficiency, safety and environmental impact near airports. This paper presents an approach to time-series flight trajectory optimization for a civil aircraft. The equations of motion are resolved by evaluating aerodynamic force prediction at each time step. The microburst effect during descent is considered in the equations of motion, and the results...
Industrial product design is characterized by increasing complexity due to the high number of involved parameters, objectives, and boundary conditions, all typically changing over time. Population-based evolutionary design optimization targets to solve these kinds of application problems, offering efficient algorithms striving for high-quality solutions. An important factor in the optimization setup...
Large social insect colonies require a wide range of important tasks to be undertaken to build and maintain the colony. Fortunately, in most nests there are many thousands of workers available to offer their assistance to ensure the expansion and survival of the colony. However, there is a crucial equilibrium between the number of workers performing each task that must not only be maintained but must...
The past few years have seen several variants of Evolutionary Algorithms (EAs) applied to solving Sudoku puzzles. Given that EAs with simple components do not work properly, considerable efforts have gone into designing ad-hoc evolutionary operators that profit from a knowledge of the problem. In this paper, we show that one of the main reasons for the improper behavior of EAs when dealing with difficult...
The Workforce Scheduling and Routing Problem refers to the assignment of personnel to visits across various geographical locations. Solving this problem demands tackling scheduling and routing constraints while aiming to minimise the total operational cost. This paper presents a Genetic Algorithm (GA) tailored to tackle a set of real-world instances of this problem. The proposed GA uses a customised...
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