• 한국콘텐츠학회논문지
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• 제11권6호
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• pp.59-66
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• 2011

자원 제약이 있는 프로젝트 스케줄링 문제는 자원의 양은 제한되어 있고 작업들 간에 선행조건이 있는 일정계획 문제로서 NP-hard 문제 중에 하나로 알려져 있다. 이러한 문제는 결정론적인 방법을 사용해서는 주어진 시간 내에 최적해를 구하기 어렵기 때문에 근사 최적해를 빠른 시간에 구할 수 있는 휴리스틱 방법을 이용한다. 본 논문에서는 자원 제약이 있는 프로젝트 스케줄링 문제를 효율적으로 해결할 수 있는 유전알고리즘을 소개한다. 제안한 유전알고리즘은 스키마 이론을 적용한 교차 연산자와 실세계 토너먼트 선택 전략을 이용하였다. 표준 문제에 실험한 결과는 제안한 알고리즘이 기존의 알고리즘 보다 우수함을 보여주었다.

• 한국경영과학회지
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• 제19권3호
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• pp.139-149
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• 1994

In many project-oriented production systems, e. g., shipyards or large-scale steel products manufacturing, resource loading by an activity is flexible, and the activity duration is a function of resource allocation. For example, if one doubles the size of the crew assigned to perform an activity, it may be feasible to complete the activity in half the duration. Such flexibility has been modeled by Weglarz [13] and by Leachman, Dincerler, and Kim [7[ in extended formulations of the resource-constrained poject scheduling problem. This paper presents a new algorithmic approach to the problem that combines the ideas proposed by the aforementioned authors. The method we propose involves a two-step approach : (1) solve the resource-constrained scheduling problem using a heuristic, and (2) using this schedule as an initial feasible solution, find improved resource allocations by solving a linear programming model. We provide computational results indicating the superiority of this approach to previous methodology for the resource-constrained scheduling problem. Extensions to the model to admit overlap relationship of the activities also are presented.

• 대한산업공학회지
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• 제10권1호
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• pp.41-45
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• 1984

A resource constrained scheduling problem that involves trade-off between resources and time is considered. Models are considered. Models are presented as zero-one integer program and objectives of models include minimum project completion time and minimum total project cost.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권1호
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• pp.20-28
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• 2012

We define a language $\mathcal{RS}$, a subclass of the scheduling language $\mathcal{RS}V$ (resource constrained project scheduling with variant processes). $\mathcal{RS}$ involves the determination of the starting times for ground activities of a project satisfying precedence and resource constraints, in order to minimize the total project duration. In $\mathcal{RS}$ ground activities and two structural symbols (operators) 'seq' and 'pll' are used to construct activity-terms representing scheduling problems. We consider three different variants for formalizing the $\mathcal{RS}$-scheduling problem, the optimizing variant, the number variant and the decision variant. Using the decision variant we show that the problem $\mathcal{RS}$ is $\mathcal{NP}$-complete. Further we show that the optimizing variant (or number variant) of the $\mathcal{RS}$-problem is computable in polynomial time iff the decision variant is computable in polynomial time.

• 한국정보시스템학회지:정보시스템연구
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• 제28권4호
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• pp.175-197
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• 2019

Purpose This study develops a heuristic algorithm to solve the time-resource tradeoffs in project scheduling problems with a real basis. Design/methodology/approach Resource constrained project scheduling problem with time-resource tradeoff is well-known as one of the NP-hard problems. Previous researchers have proposed heuristic that minimize Makespan of project scheduling by deriving optimal combinations from finite combinations of time and resource. We studied to solve project scheduling problems by deriving optimal values from infinite combinations. Findings We developed heuristic algorithm named Push Algorithm that derives optimal combinations from infinite combinations of time and resources. Developed heuristic algorithm based on simulated annealing shows better improved results than genetic algorithm and further research suggestion was discussed as a project scheduling problem with multiple resources of real numbers.

• 대한산업공학회지
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• 제37권4호
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• pp.408-414
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• 2011

The objective of this paper is to define local optimization algorithms (LOA) to solve Resource-Constrained Project Scheduling Problem (RCPSP) and analyze the performance of these algorithms. By representing solutions with activity list, three primitive LOAs, i.e. forward and backward improvement-based, exchange-based, and relocation-based LOAs are defined. Also, combined LOAs integrating two primitive LOAs are developed. From the experiments with standard test set J120 generated using ProGen, the FBI-based LOA demonstrates to be an efficient algorithm. Moreover, algorithms combined with FBI-based LOA and other LOA generate good solutions in general. Among the considered algorithms, the combined algorithm of FBI-based and exchangebased shows best performance in terms of solution quality and computation time.

• 한국건설관리학회논문집
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• 제8권6호
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• pp.235-245
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• 2007

This research study presents the development and application of an Elitist Genetic Algorithm (Elitist GA) for solving the resource-constrained project scheduling problem, which is one of the most challenging problems in construction engineering. Main features of the developed algorithm are that the elitist roulette selection operator is developed to preserve the best individual solution for the next generation so as to obtain the improved solution, and that parallel schedule generation scheme is used to generate a feasible solution to the problem. The experimental results on standard problem sets indicate that the proposed algorithm not only produces reasonably good solutions to the problems over the heuristic method and other GA, but also can find the optimal and/or near optimal solutions for the large-sized problems with multiple resources within a reasonable amount of time that will be applicable to the construction industry. This paper will help researchers and/or practitioners in the construction project scheduling software area with alternative means to find the optimal schedules by utilizing the advantages of the Elitist GA.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.881-885
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• 2005

Scheduling repetitive projects under limitations on the amounts of available resources (labor and equipment) has been an active subject because of its practical relevance. Traditionally, the limitation is specified as a deterministic (fixed) number, such as 1000 labor-hours. The limitation, however, is often exposed to uncertainty and variability, especially when the project is lengthy. This paper presents a stochastic optimization model to treat the situations where the limitations of resources are expressed as probability functions in lieu of deterministic numbers. The proposed model transfers each deterministic resource constraint into a corresponding stochastic one and then solves the problem by the use of a chance-constrained programming technique. The solution is validated by comparison with simulation results to show that it can satisfy the resource constraints with a probability beyond the desired confidence level.

• Industrial Engineering and Management Systems
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• 제9권2호
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• pp.70-79
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• 2010

Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.181-195
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• 2006

Resource-constrained project scheduling problems with variant processes can be represented and solved using a logic-based terminological language called RSV (resource constrained project scheduling with variant processes). We consider three different variants for formalizing the RSV-scheduling problem, the optimizing variant, the number variant and the decision variant. Using the decision variant we show that the RSV- problem is NP-complete. Further we show that the optimizing variant (or number variant) of the RSV-problem is computable in polynomial time iff. the decision variant is computable in polynomial time.