Multiobjective Optimization Using Flower Pollination Algorithm for Storage Location Assignment at Lazada Thailand Warehouse

Storage is a key task of a logistics enterprise. Effective storage processes can increase the efficiency of enterprise logistics processes and positively affect logistics costs. Therefore, it is very important to deal with selecting storage locations within the enterprise area. The present paper deals with the optimal in-house storage location. The research was realized through a Czech Republic brewing company case study which aimed to find and select the best in-house storage location. The decision-making methods chosen for this solution were the additive ratio assessment method and the combined compromised solution method. While these methods are rarely used for this kind of solution-making, they helped to find the best location for reasonable storage in the research enterprise.

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A Sustainable Location-Allocation Model for Solar-Powered Pest Control to Increase Rice Productivity

Ramadhan

Sutopo

Hisjam

2022

ASI

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Insect attacks are a very complicated problem in rice cultivation that cause a decrease in rice productivity. It is very important to not use pesticides to kill pests due to environmental and health issues. This study aimed to solve the pest problem by installing solar-powered pest-control technology using waves of ultraviolet light and ultrasonic sound (UVUS, the name of the product). The development of UVUS involved not only innovation from startups but also the adaption of existing technologies such as batteries, solar panels, and sensors. A location-allocation model has been developed in accordance with a flower pollination algorithm (FPA) and sustainability considerations to solve the problem of rice productivity using the innovative technology of solar-powered pest control. The mixed-integer linear programming (MILP) approach was used to determine the number of UVUS required to minimize the areas missed by the ultraviolet light and ultrasonic sound. Numerical analysis of a case study of Delanggu Village showed that the model can be used to determine the number of UVUS required to only miss a certain minimal area. The results show that the proposed model can be applied to solve pest control and can provide promising economical, social, and environmental outcomes.

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Multiobjective Optimization Using Flower Pollination Algorithm for Storage Location Assignment at Lazada Thailand Warehouse

Cited by 3 publications

References 9 publications

Predicting Warehouse Location of Online Shopping Platforms with Machine Learning Algorithm – A Case Study

Predicting Warehouse Location of Online Shopping Platforms with Machine Learning Algorithm – A Case Study

Multi-Criteria Decision-Making Techniques for Optimal In-House Storage Location Selection

A Sustainable Location-Allocation Model for Solar-Powered Pest Control to Increase Rice Productivity

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