Dual command cycle dynamic sequencing method to consider GHG efficiency in unit-load multiple-rack automated storage and retrieval systems

作者：Nia Ali Roozbeh; Haleh Hassan^*; Saghaei Abbas

来源：COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 111: 89-108.

DOI：10.1016/j.cie.2017.07.007

• Ant colony optimization (ACO)
• Automated storage and retrieval systems (AS/RS)
• Dual command (DC) cycle
• Dynamic sequencing
• Genetic algorithm (GA)
• Greenhouse gas (GHG) emissions

In some AS/RS, the S/R machine executes a storage request and then a retrieval request to form a dual command (DC) cycle. This paper deals with a DC cycle "dynamic sequencing" method in unit-load multiple-rack AS/RS system. To create a kind of greenhouse gas (GHG) efficiency in the model, tax cost, penalty cost and discount of produced GHG emissions, limitations on available time of all facilities and total permitted GHG emissions produced by all equipment are considered in the model. In addition, an ant colony optimization (ACO) is employed to find a near-optimum solution of proposed mathematical model with the objective of minimizing the total cost of the GHG efficiency in AS/RS. Since no benchmark is available in the literature, a genetic algorithm (GA) is developed as well to validate the result obtained. For further validation, warehouse throughput rate in terms of time and cost is calculated for the model. At the end, twenty numerical examples are presented to demonstrate the application of the proposed methodology. Our results verified that GA was able to find better and nearer optimal solutions.

• 出版日期2017-9