A Distributed Algorithm for 0-1 Knapsack Problem Based on Mobile Agent

Qiao, Shanping; Wang, Shixian; Lin, Yongzheng; Zhao, Lei

doi:10.1109/isda.2008.110

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…To our knowledge, very few papers addressing the solving of knapsacks problem family by multi-agents systems are available. In [34], a distributed algorithm is proposed for the 0 − 1 knapsack problem based on the mobile agent, and it is feasible and effective in theoretical analysis. The authors combine the mobile agent technology with a traditional parallel algorithm of the knapsack problems.…”

Section: Related Workmentioning

confidence: 99%

Smart Agents for the Multidimensional Multi-choice Knapsack Problem

Htiouech¹,

Alzaidi²

2017

IJCA

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In this paper, we propose a multi-agent approach for solving the multidimensional multi-choice knapsack problem (called MMKP). The MMKP is an NP-Hard optimization problem in strong sense. It is considered as a combination of two other variants such as: the multi-choice knapsack problem (MCKP) and the multidimensional knapsack problem (MDKP). The MMKP can be applied in many problems in real world. It can model many industrial situations, such as capital budgeting, model of allocation resources and finance. The particular properties of the MMKP favor its decomposition into many MMKP sub-problems with small sizes. The assignment of sub-problems and the sharing of available resources are allocated to a first agent. Each subproblem is then solved by an agent. To work collaboratively, a strategic negotiation between agents has been defined. A coordinator agent (CA) will evaluate and merge the generated solutions to build a feasible solution to the initial problem. The choice rules of the CA is modeled as a multidimensional knapsack problem (MKP). The proposed method is able to solve several instances of literature effectively, in particular for large size instances. General TermsMetaheuristic, knapsack problem

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Section: Related Workmentioning

confidence: 99%

Smart Agents for the Multidimensional Multi-choice Knapsack Problem

Htiouech¹,

Alzaidi²

2017

IJCA

View full text Add to dashboard Cite

show abstract

“…Specifically, the time complexity is O(2 n ) in the worst case. So, it is important to design an effective approximation algorithm for solving the KP (Qiao et al, 2008). Several works in literature used GAs combined with other methods to solve the 0-1 KP.…”

Section: Prior Workmentioning

confidence: 99%

“…This is a bio-inspired optimisation algorithm based on group intelligence. In Qiao et al (2008), the authors combine the mobile agent technology with the traditional parallel algorithm which enables changing the parallel process handled in a parallel computer to the process performed by several ordinary computers, and by doing so avoid the restrictions of the limited computational resources. In Jun and Jian (2009), a discrete binary version of differential evolution (DBDE) was employed, where each component of a mutated vector component changes with the differential probability and will take on a zero or one value.…”

Section: Prior Workmentioning

confidence: 99%