• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.218-224
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• 2014

The logic-based scheduling language RCPSV may be used to model resource-constrained project scheduling problems with variants for minimizing the project completion time. A diagram-based, nonredundant enumeration algorithm for the RCPSV-problem is proposed and the correctness of the algorithm is proved.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.744-747
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• 2005

The AEC (Architecture/Engineering/Construction) industry is facing a competitive world after it entered into the 21^st century. Due to improper planning and scheduling, the construction projects face severe delays in completion. Most of the present day construction organisations operate in multiple project environments where more than one projects are to be managed simultaneously. But the advantages of planning and scheduling as multiple projects have not been utilized by these organisations. Change in multi-project planning and scheduling is inevitable and often frequent, therefore the traditional planning and scheduling approaches are no more feasible in scheduling multiple construction projects. The traditional scheduling tools like CPM and PERT do not offer any help in scheduling in a resource-constrained environment. This necessitated a detailed study to model the environment realistically and to make the allocation of limited resources flexible and efficient. This paper delineates about the proactive model which will help the project managers for scheduling the multiple construction projects.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.410-420
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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 [131 and by Leachman, Dincerler, and Kim [7] in extended formulations of the resource-constrained project 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 relationships of the activities also are presented.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.1-11
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• 2017

Stochastic resource-constrained project scheduling problem is an extension of resource-constrained project scheduling problem such that activity duration has stochastic nature. In real situation where activity duration is not known until the activity is finished, open-loop based static policies such as activity-based policy and priority-based policy will not well cope with duration variability. Then, a dynamic policy based on closed-loop decision making will be regarded as an alternative toward achievement of minimal makespan. In this study, a dynamic policy designed to select activities to start at each decision time point is illustrated. The performance of static and dynamic policies based on variable neighborhood search is evaluated under the discrete-event simulation environment. Experiments with J120 sets in PSPLIB and several probability distributions of activity duration show that the dynamic policy is superior to static policies. Even when the variability is high, the dynamic policy provides stable and good solutions.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.739-748
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• 2007

The objective of this research study is to develop the permutation-based genetic algorithm for solving the resource-constrained project scheduling problem in construction engineering by incorporating elitism into genetic algorithm. A key aspect of the algorithm was the development of the elitist roulette selection operator to preserve the best individual solution for the next generation so the improved solution can be obtained. Another notable characteristic is the application of the parallel schedule generation scheme to generate a feasible solution to the problem. Case studies with a standard test problem were presented to demonstrate the performance and accuracy of the algorithm. The computational results indicate that the proposed algorithm produces reasonably good solutions for the resource-constrained project scheduling problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3638-3657
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• 2022

In urban vehicular edge computing (VEC) environments, one edge server always serves many task requests in its coverage which results in the resource-constrained problem. To resolve the problem and improve system utilization, we first design a general hierarchical resource management framework based on typical VEC network structures. Following the framework, a specific interacting protocol is also designed for our decision algorithm. Secondly, a greedy bidding-based multi-hop task scheduling decision algorithm is proposed to realize effective task scheduling in resource-constrained VEC environments. In this algorithm, the goal of maximizing system utility is modeled as an optimization problem with the constraints of task deadlines and available computing resources. Then, an auction mechanism named greedy bidding is used to match task requests to edge servers in the case of multiple hops to maximize the system utility. Simulation results show that our proposal can maximize the number of tasks served in resource constrained VEC networks and improve the system utility.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.735-737
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• 2009

Efficient scheduling for project is a major concern for software engineers. Industries simultaneously try to perform a variety method of projects with the resource-constrained scheduling. In this paper, genetic algorithm is presented to solve the scheduling problem of the resource-constrained scheduling and is substantiated with results.

• IE interfaces
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• v.13 no.1
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• pp.110-119
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• 2000

Resource-constrained project scheduling is to allocate limited resources to activities to optimize certain objective functions and to determine a start time for each activity in the project such that precedence constraints and resource requirements are satisfied. This study suggests a multi-project scheduling model which can level work loads, make the most of production capacity and restrain the delay of delivery by developing a heuristic algorithm which minimizes the project completion time and maximizes the load rate under resource constraints.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.59-66
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• 2011

Resource constrained project scheduling problem with multiple resource constraints as well as precedence constraints is well-known as one of the NP-hard problem. Since these problems can't be solved by the deterministic method during reasonable time, the heuristics are generally used for getting a sub-optimal during reasonable time. In this paper, we introduce an efficient genetic algorithm for resource constrained project scheduling problem using crossover which is applying schema theory and real world tournament selection strategy. Experimental results showed that the proposed algorithm is superior to conventional algorithm.