Shipping route problem is a vital problem for maximizing the profits in sea transportation, which can be essentially regarded as a multi-objective optimization problem. In this work, a model of shipping route optimiza...
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Shipping route problem is a vital problem for maximizing the profits in sea transportation, which can be essentially regarded as a multi-objective optimization problem. In this work, a model of shipping route optimization problem is established, and then an efficient approach called membranealgorithm is introduced to solve the problem, which is inspired from the behaviors of chemicals communicating among living cells. We test our method on a simulated data experiment. Experimental results show that our method can efficiently find the globally optimal route and performs superior to the genetic algorithm and ant colony algorithm.
Nowadays, an increasing number of vehicle routing problem with stochastic demands (VRPSD) models have been studied to meet realistic needs in the field of logistics. In this paper, a bi-objective vehicle routing probl...
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Nowadays, an increasing number of vehicle routing problem with stochastic demands (VRPSD) models have been studied to meet realistic needs in the field of logistics. In this paper, a bi-objective vehicle routing problem with stochastic demands (BO-VRPSD) was investigated, which aims to minimize total cost and customer dissatisfaction. Different from traditional vehicle routing problem (VRP) models, both the uncertainty in customer demands and the nature of multiple objectives make the problem more challenging. To cope with BO-VRPSD, a membrane-inspired multi-objective algorithm (MIMOA) was proposed, which is characterized by a parallel distributed framework with two operation subsystems and one control subsystem, respectively. In particular, the operation subsystems leverage a multi-objective evolutionary algorithm with clustering strategy to reduce the chance of inferior solutions. Meanwhile, the control subsystem exploits a guiding strategy as the communication rule to adjust the searching directions of the operation subsystems. Experimental results based on the ten 120-node instances with real geographic locations in Beijing show that, MIMOA is more superior in solving BO-VRPSD to other classical multi-objective evolutionary algorithms.
Cloud computing is an emerging technology in computing that provides different services over the Internet. It needs composite services to perform a complex task. Optimal selection of services that provides both functi...
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Cloud computing is an emerging technology in computing that provides different services over the Internet. It needs composite services to perform a complex task. Optimal selection of services that provides both functionality and nonfunctionality requirements is an NP-hard problem. This study uses nondeterministic parallel and distributed structures of membrane systems for the recently improved multiverse optimization algorithm to improve the quality of solutions. In the previous membrane-inspired algorithm, the population was divided into subpopulations that evolve different dynamic membranes. This study not only uses a conventional membrane-inspired approach to introduce a conventional membrane-inspired multiverse optimizer (CMIMVO) for the first time but also proposes an algorithm that divides the variables (dimension) into subgroups for different membranes called proposed membrane-inspired multiverse optimizer (PMIMVO). Thus, in PMIMVO, each membrane works on a subgroup to gain global information, which considers the best values obtained by other membranes for other variables. The PMIMVO shows promising results on benchmark function problems. Furthermore, simulation results show that the PMIMVO approach could achieve up to 38% improvement in integrated quality of service (QoS) with attributes including response time, price, availability, and reliability in comparison with the previous approaches, including genetics algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), moth-flame optimization (MFO) improved multiverse optimizer (MVO), and CMIMVO.
Shipping route problem is a vital problem for maximizing the profits in sea transportation, which can be essentially regarded as a multi-objective optimization problem. In this work, a model of shipping route optimiza...
详细信息
ISBN:
(纸本)9783662450482
Shipping route problem is a vital problem for maximizing the profits in sea transportation, which can be essentially regarded as a multi-objective optimization problem. In this work, a model of shipping route optimization problem is established, and then an efficient approach called membranealgorithm is introduced to solve the problem, which is inspired from the behaviors of chemicals communicating among living cells. We test our method on a simulated data experiment. Experimental results show that our method can efficiently find the globally optimal route and performs superior to the genetic algorithm and ant colony algorithm.
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