Algorithms with guarantee value for knapsack problems

Guler, Asli; Nurıyev, Urfat; Berberler, Murat Erşen; Nuriyeva, Fidan

doi:10.1080/02331934.2011.617818

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Bansal and Deep (2012) proposed a modified binary particle swarm optimization for KP and report promising results. Guler et al (2012) presented algorithm with guarantee value for KPs. Truong et al (2013) applied chemical reaction optimization algorithm with greedy strategy for the 0-1KP.…”

Section: Literature Reviewmentioning

confidence: 99%

A Rough Sets based modified Scatter Search algorithm for solving 0-1 Knapsack problem

Rezazadeh

2015

10.5267/j.dsl

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This paper presents a new search methodology for different sizes of 0-1 Knapsack Problem (KP). The proposed methodology uses a modified scatter search as a meta-heuristic algorithm. Moreover, rough set theory is implemented to improve the initial features of scatter search. Thereby, the preliminary results of applying the proposed approach on some benchmark dataset appear that the proposed method was capable of providing better results in terms of time and quality of solutions.

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Section: Literature Reviewmentioning

confidence: 99%

A Rough Sets based modified Scatter Search algorithm for solving 0-1 Knapsack problem

Rezazadeh

2015

10.5267/j.dsl

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“…The authors combined algorithms from discrete optimization with algorithms from continuous optimization. In [11], greedy algorithms for the knapsack problem were considered and improved approximation ratios for different variants of the problem were derived. Some applications of AI techniques to generation planning and investment were described in [12].…”

Section: Introductionmentioning

confidence: 99%

A new effective dynamic program for an investment optimization problem

Gafarov

Dolgui²,

Lazarev

et al. 2016

Autom Remote Control

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International audienceAfter a series of publications of T.E. O'Neil et al. (e.g. in 2010), dynamic programming seems to be the most promising way to solve knapsack problems. Some techniques are known to make dynamic programming algorithms (DPA) faster. One of them is the graphical method that deals with piecewise linear Bellman functions. For some problems, it was previously shown that the graph-ical algorithm has a smaller running time in comparison with the classical DPA and also some other advantages. In this paper, an exact graphical algorithm (GrA) and a fully polynomial-time approximation scheme based on it are presented for an investment optimization problem having the best known running time. The algorithms are based on new Bellman functional equations and a new way of implementing the GrA

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Complementary Problems for Subset-Sum and Change Making Problems

Guler

Nurıyev

2013

Advances in Intelligent Systems and Computing

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Algorithms with guarantee value for knapsack problems

Cited by 3 publications

References 6 publications

A Rough Sets based modified Scatter Search algorithm for solving 0-1 Knapsack problem

A Rough Sets based modified Scatter Search algorithm for solving 0-1 Knapsack problem

A new effective dynamic program for an investment optimization problem

Complementary Problems for Subset-Sum and Change Making Problems

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