• 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.

• 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.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.735-737
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• 2009

소프트 엔지니어링에서 프로젝트에 대한 효과적인 스케줄링은 중요한 부분 중에 하나이다. 산업에서는 한정된 자원에 대한 스케줄링을 가지는 다양한 방법이 시도 되고 있다. 본 논문에서는 유전자 알고리즘을 사용한 한정된 자원을 가지는 프로젝트 스케줄링에 대한 접근 방법을 제안하고, 실험 결과를 통하여 그 효과성을 입증한다.

• 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.

• 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.

• 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.

• 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.

• 산업경영시스템학회지
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• 제14권23호
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• pp.19-25
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• 1991

In this paper, constrained resource project scheduling problems schedule project activities subject to finite constraints on the availability of non-storable resource. Further, resources are assumed to be available per period in constant amounts, and are also demanded by an activity in constant amounts throughout the duration of the activity. We describe formulation which minimizes the combined cost of fluctuations in resource demand and delay of project completion. Cost bounding procedures are augmented by dominance relationships presented as theorems. This paper presents algorithm for solving the problem. And numerical examples are presented. Sensitivity analysis to evaluate the effect of changes of cost efficients is conducted.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.