• 대한산업공학회지
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• 제27권1호
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• pp.25-29
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• 2001

We present a two dimensional linear programming knapsack problem with the extended GUB constraint. The presented problem is an extension of the cardinality constrained linear programming knapsack problem. We identify some new properties of the problem and derive a solution algorithm based on the parametric analysis for the knapsack right-hand-side. The solution algorithm has a worst case time complexity of order O($n^2logn$). A numerical example is given.

• 산업경영시스템학회지
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• 제19권40호
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• pp.137-142
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• 1996

An algorithm for solving the cardinality constrained linear programming knapsack problem is presented. The algorithm has a convenient structure for a branch-and-bound approach to the integer version, especially to the 0-1 collapsing knapsack problem. A numerical example is given.

• 융합보안논문지
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• 제14권7호
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• pp.59-64
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• 2014

이 논문에서는 고정된 개수를 가진 bin들을 이용하여 실행 복잡도가 $p(n){\cdot}2^{O(\sqrt{n})}$인 알고리즘을 제시한다, 여기서 x는 (5)n개의 객체들에 대한 리스트의 길이에 대한 총 비트 수를 나타낸다. 이러한 방법은 수치적 크기나 비중의 합의 리스트를 이용하는 여러 가지 최적화 알고리즘이나 결정 문제등에 적용할 수 있다. 이 논문에서 제시한 알고리즘은 의사-다항식(pseudo-polynomial) 시간을 갖는 NP-Complete의 많은 문제들을 결정적인 서브-지수 시간에 해결할 수 있은 가능성을 제시한다. 여기서 제시한 알고리즘을 이용하여 생명공학의 유전자 분석에 적용하려고 한다.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.665-676
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• 2022

In modern logistics, the effective use of the vehicle volume and loading capacity will reduce the logistic cost. Many heuristic algorithms can solve this knapsack problem, but lots of these algorithms have a drawback, that is, they often fall into locally optimal solutions. A fusion optimization method based on simulated annealing algorithm (SA) and binary particle swarm optimization algorithm (BPSO) is proposed in the paper. We establish a logistics knapsack model of the fusion optimization algorithm. Then, a new model of express logistics simulation system is used for comparing three algorithms. The experiment verifies the effectiveness of the algorithm proposed in this paper. The experimental results show that the use of BPSO-SA algorithm can improve the utilization rate and the load rate of logistics distribution vehicles. So, the number of vehicles used for distribution and the average driving distance will be reduced. The purposes of the logistics knapsack problem optimization are achieved.

• 한국통신학회논문지
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• 제16권9호
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• pp.883-892
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• 1991

본 논문에서는 공개키 시스템을 위한 새로운 knapsack 알고리즘의 설명과 난이도 시험 및 이를 구현하기 위한 병렬 구조를 제안하였다. 기존의 Merkle Hellmand의 knapsack은 선형 대수법에 의한 다른 쉬운 수열로의 사상 효과 등으로 Shamir나 Brieckell 등의 attack에 약했으나, 선형 이동 knapsack 시스템은 이러한 약점을 보완한다. 그리고 Brickell 및 Lagarias, Odlyzko의 저밀도 attack 알고리즘의 구현으로 새로운 knapsack 시스템과 기존의 knapsack 시스템을 비교 평가하였다. 또한 이 선형 이동 knapsack 시스템의 병렬 구현을 위한 VLSI 구조를 제안하였다.

• Nonlinear Functional Analysis and Applications
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• 제26권3호
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• pp.611-628
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• 2021

In this paper, we propose a new branch-reduction-and-bound algorithm to solve the nonlinear knapsack problems by using general discrete monotonic optimization techniques. The specific properties of the problem are exploited to increase the efficiency of the algorithm. Computational experiments of the algorithm on problems with up to 30 variables and 5 different constraints are reported.

• Management Science and Financial Engineering
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• 제14권1호
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• pp.91-96
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• 2008

Robust knapsack problem appears when dealing with data uncertainty on the knapsack constraint. This note presents a generalization of the cover inequality for the problem with its lifting procedure. Specifically, we show that the lifting can be done in a polynomial time as in the usual knapsack problem. The results can serve as a building block in devising an efficient branch-and-cut algorithm for the general robust (0, 1) IP problem.

• 대한산업공학회지
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• 제23권4호
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• pp.661-667
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• 1997

We consider a generalized problem of the continuous multiple choice knapsack problem and study on the LP relaxation of the candidate problems which are generated in the branch and bound algorithm for solving the generalized problem. The LP relaxed candidate problem is called the generalized continuous multiple choice linear knapsack problem and characterized by some variables which are partitioned into continuous multiple choice constraints and the others which only belong to simple upper bound constraints. An efficient algorithm of order O($n^2logn$) is developed by exploiting some structural properties and applying binary search to ordered solution sets, where n is the total number of variables. A numerical example is presented.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.773-774
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• 2005

The knapsack problem (KP) is one of the traditional optimization problems. Specially, multiconstrained knapsack problem (MKP) is well-known NP-hard problem. Many heuristic algorithms and evolutionary algorithms have tackled this problem and shown good performance. This paper presents a novel genetic algorithm for the multiconstrained knapsack problem. The proposed algorithm is called 'Adaptive Link Adjustment'. It is based on integer random key representation and uses additional ${\alpha}$ and ${\beta}$-process as well as selection, crossover and mutation. The experiment results show that it can be archive good performance.

• 한국경영과학회지
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• 제31권1호
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• pp.55-71
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• 2006

We perform a computational study on 0-1 knapsack problems generated under explicit correlation induction. A total of 2000 100-variable test problems are solved. We use two solution methods: (1) a well known heuristic and (2) a representative branch and bound type algorithm. Two different performance measures are considered: (1) the number of nodes needed to find an optimal solution and (2) the relative error of the heuristic solution. We also examine the effect of different joint probability mass functions (pmfs) for the coefficient values on the performance of the solution procedure.