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Stochastic ranking is a promising technique for handling constraints in constrained evolutionary optimization. In stochastic ranking, the comparison between a pair of individuals is randomly based on either their objective values or degrees of constraint violation according to a constant probability parameter. In this paper, an adaptive stochastic ranking mechanism is presented to solve constrained...
This paper develops an opposition-based learning harmony search algorithm with mutation (OLHS-M) for solving global continuous optimization problems. The proposed method is different from the original harmony search (HS) in three aspects. Firstly, opposition-based learning technique is incorporated to the process of improvisation to enlarge the algorithm search space. Then, a new modified mutation...
In this paper, we propose a new algorithm Label based Ant Colony System (LACS) based on the multi-attribute label (MAL) algorithm and multi ant colony system (MACS) algorithm to address the multi-attribute vehicle routing problem with heterogeneous fleet, backhaul and mixed-load (MAHVRPBM). Leveraging the object-oriented principle, we build multi-attribute labels for various customers (demands), vehicles...
The existing literature on path optimization of emergency material transportation is either indefinite path optimization question of emergency material from the single emergency service point to the single emergency demand point or deterministic path optimization question from the single emergency service point to many emergency demand points. This paper aims to study enclosed path optimization question...
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