A genetic algorithm for determining optimal replenishment cycles to minimize maximum warehouse space requirements☆

Yao, Ming-Jong; Chu, Weng Ming

doi:10.1016/j.omega.2007.01.007

Cited by 43 publications

(11 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The most of them are based on genetic algorithm and fuzzy logic system. Yao et al [9] proposes an idea of the optimal cycles, in order to the optimal use of warehouse space in warehouse replenishment time was introduced and the genetic algorithm was used to find the best cycle to reduce the maximum required space in the warehouse. Farahani and Elahipanah [10] presented a solution for a distributed network of JIT (Just in Time).…”

Section: State Of the Artmentioning

confidence: 99%

Optimal control of storage system based on intelligent techniques

Tsagaris

2014

2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR)

View full text Add to dashboard Cite

In order to obtain high productivity industrial automatic storage systems should complete the storage tasks in minimum of time with the maximum of performance. Optimization is the key point of this problem. This paper proposes a method for intelligent storage system, which optimizes the storing process by deciding the optimum slot that an object will occupy in a warehouse. Depending on the weight, each object has to be stored in a different space. The method is based on genetic algorithm. Genetic algorithms are used in order to optimise the allocation of storage slots at the shortest time. The duration of storage is monitored and used as feedback to the system so as to optimize the algorithm. The system is integrated with PLC and custom SCADA system which gathered the necessary information from the PLC via an OPC server. Any delay of the system is taken into account using feedback of the completion time, so that the operation error is introduced in the application, which is trained to improve its operation in the next loop. The proposed framework improves the placement of objects in specific warehouse slots.

show abstract

Section: State Of the Artmentioning

confidence: 99%

Optimal control of storage system based on intelligent techniques

Tsagaris

2014

2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR)

View full text Add to dashboard Cite

show abstract

“…In the first case, the MCRSDP-GA is compared with the implicit enumeration approach (IEA) to show its computational efficiency. The MCRSDP-GA is also compared with the random solution generation (RSG) approach in the other three cases, where the RSG keeps searching for a better solution by randomly producing solutions without evolution process [40]. The MCRSDP-GA, the IEA, and the RSG are all programmed in MATLAB and are executed on a personal computer with Intel Core 2 Quad CPU 2.4G and 2G RAM.…”

Section: Numerical Experiments and Applicationsmentioning

confidence: 99%

Using minimal cuts to optimize network reliability for a stochastic computer network subject to assignment budget

Lin

Yeh

2011

Computers & Operations Research

View full text Add to dashboard Cite

“…demands are met for all products required at all periods. The constraints (12) are the flow conservation at depots. The constraints (13) show amount of stored product at the end of period.…”

Section: Notationsmentioning

confidence: 99%

“…Supply chain modeling offers short-, medium-or long-term optimization potentials. Elements within the optimization scope may be plants, distribution centers, suppliers, customers, orders, products, or inventories [12]. The standard problems for supply chain modeling are formulated in the following manner.…”

Section: Introductionmentioning

confidence: 99%

An Interactive Allocation for Depot-Customer-Depot in a Multi Aspect Supply Chain Network

Mohajeri¹,

Mahdavi

Fazlollahtabar

2011

IJE

View full text Add to dashboard Cite

Supply chain excellence has a real huge impact on business strategy. Building supply chains (SCs) as flexible system represents one of the most exciting opportunities to create value. This requires integrated decision making amongst autonomous chain partners with effective decision knowledge sharing among them. The key to success lies in knowing which decision has more impact on the supply chains performance. Here, we propose a supply chain which considers multiple depots, multiple vehicles, multiple products, multiple customers, and different time periods. This paper presents a mathematical model for selecting the appropriate depots among candidate depots, the allocation of orders to depots and vehicles, also the allocation of the returning vehicles to depots, to minimize the total costs.

show abstract

A genetic algorithm for determining optimal replenishment cycles to minimize maximum warehouse space requirements☆

Cited by 43 publications

References 17 publications

Optimal control of storage system based on intelligent techniques

Optimal control of storage system based on intelligent techniques

Using minimal cuts to optimize network reliability for a stochastic computer network subject to assignment budget

An Interactive Allocation for Depot-Customer-Depot in a Multi Aspect Supply Chain Network

Contact Info

Product

Resources

About