Transformer has shown excellent performance in remote sensing field with long-range
modeling capabilities. Remote sensing video (RSV) moving object detection and tracking …

This paper provides a survey of the research done on optimization in dynamic environments
over the past decade. We show an analysis of the most commonly used problems, methods …

In real-world applications, there are many fields involving dynamic multi-objective
optimization problems (DMOPs), in which objectives are in conflict with each other and …

Dynamic multiobjective optimization deals with simultaneous optimization of multiple
conflicting objectives that change over time. Several response strategies for dynamic …

Big data technology has undoubtedly accelerated the efficiency of data processing, made
data become an important reference basis in enterprise operation, and changed the mode of …

The Case-Based Reasoning (CBR) solves problems by using the past problem solving
experiences. How to apply these experiences depends on the type of the problem. The …

When memory-based evolutionary algorithms are applied in dynamic environments, the
certainly use of uncertain prior knowledge for future environments may mislead the …

Genetic Algorithm (GA) is well-known optimization algorithm for solving various kinds of the
optimization problem. GA is based on evolutionary principles and effectively solves the large …

This paper presents a new evolutionary dynamic optimization algorithm, holographic
memory-based Bayesian optimization algorithm (HM-BOA), whose objective is to address …

EVOLUTIONARY ALGORITHMS FOR SUPPLY CHAIN OPTIMISATION Page 1
EVOLUTIONARY ALGORITHMS FOR SUPPLY CHAIN OPTIMISATION Maksud Ibrahimov …