Conference Agenda

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Session Overview
D2S3T3: Models and Algorithms
Thursday, 24/Feb/2022:
2:45pm - 3:45pm

Session Chair: Tobias Sprodowski

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2:45pm - 3:15pm
ID: 141 / D2S3T3: 1
Full Paper LDIC Submission
LDIC 2022 Topics: Modeling and Optimization Methods
Keywords: Optimisation, evolutionary algorithm, domain knowledge, constraint-handling

Choosing the right technique for the right restriction - a domain-specific approach for enforcing search-space restrictions in evolutionary algorithms

Plump, Christina1,2; Berger, Bernhard J.3; Drechsler, Rolf1,2

1Institute of Computer Science, University Bremen, Germany; 2DFKI GmbH, Bremen, Germany; 3Institute of Embedded Systems, Hamburg University of Technology, Germany

Evolutionary algorithms are a well-known tool for optimising problems that are hard to solve. They mirror the evolutionary approach of recombination and mutation as well as a selection process according to the fitness of an individual. Individuals who violate set search space restrictions are either killed at birth or penalised in their fitness calculation. Which possibility is best to choose depends on the problem at hand and therefore subject to change. Furthermore, restrictions can be vague, for example, when stemming from experiments. We propose a noise-sensitive penalty for violating restrictions and develop a framework where an expert might choose which penalising technique to choose for what kind of restriction. We evaluate our configurable approach against configurations where one technique is used for every type of restriction and find that our approach achieves better results than a strict configuration. Additionally, the noise-sensitive penalising method allows individuals to survive, which may only violate the given restrictions due to a noised testing environment, leading to better results.

3:15pm - 3:45pm
ID: 119 / D2S3T3: 2
Full Paper LDIC Submission
LDIC 2022 Topics: Cyber-Physical Systems and Material Flow Systems
Keywords: Stochastic process, Cargo throughput capacity, Semi-Markov jump system, Robust filter

A cargo throughput capacity quantization estimation using semi-Markov jump system filter within partial state delay

Ren, Bingxuan1; Yin, Tangwen1; KARIMI, HAMID REZA2; Fu, Shan1

1Shanghai JiaoTong University; 2Politecnico di Milano

Cargo throughput capacity is a very important and basic indicator for port expansion and operation and maintenance. As a non-linear dynamic indicator affected by multiple variables, timely estimation of cargo throughput capacity can schedule the usage of quay cranes, thereby reducing port energy consumption. In order to solve the estimation of the long-term scale unit, to complete the estimation in the multi-modal situation through the method of system evolution and to include the quay crane scheduled situation into system, we propose a filter within partial state delay to estimate the throughput capacity based on the semi-Markov jump systems. Through the non-exponential transition probability and quantization, the multi-modal estimation method is designed. The Hinf stability can be assured under the conditions provided by Lyapunov approach. Numerical results show that our methods could provide a different prospect and satisfied performance in the throughput capacity quantization estimation.

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