作者：
Zhu, JieLi, XiaopingShen, WeimingSoutheast Univ
Sch Comp Sci & Engn Nanjing Jiangsu Peoples R China Southeast Univ
Key Lab Comp Network & Informat Integrat Minist Educ Nanjing Jiangsu Peoples R China CNR
Ctr Computer Assisted Construct Technol London ON Canada
In this paper, a specific preemptive resource-constrained project scheduling problem (PRCPSP) with makespan minimization is considered of which each activity could be interrupted at most M times. According to activity...
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In this paper, a specific preemptive resource-constrained project scheduling problem (PRCPSP) with makespan minimization is considered of which each activity could be interrupted at most M times. According to activity requirements and resource availability, resources are allocated to activities in different intervals. A resource-fragment chain is constructed to keep resource states dynamically. The resource allocation problem is transferred to the well-known 0-1 knapsack problem and solved by dynamic programming in pseudo-polynomial time complexity. The schedule enhancement method is developed to further improve the quality of obtained schedules by removing and rescheduling each activity in the activity list. By integrating the resource allocation and the schedule enhancement method, a genetic algorithm is proposed for the considered problem with the objective to minimize makespan. Computational experiments on the standard J30 and J120 sets show that the proposed algorithm is amongst the most competitive algorithms in literature for the pre-emptive cases.
The global cumulative constraint was proposed for modelling cumulative resources in schedulingproblems for finite domain (FD) propagation. Since that time a great deal of research has investigated new stronger and fa...
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The global cumulative constraint was proposed for modelling cumulative resources in schedulingproblems for finite domain (FD) propagation. Since that time a great deal of research has investigated new stronger and faster filtering techniques for cumulative, but still most of these techniques only pay off in limited cases or are not scalable. Recently, the "lazy clause generation" hybrid solving approach has been devised which allows a finite domain propagation engine possible to take advantage of advanced SAT technology, by "lazily" creating a SAT model of an FD problem as computation progresses. This allows the solver to make use of SAT explanation and autonomous search capabilities. In this article we show how, once we use lazy clause generation, modelling the cumulative constraint by decomposition creates a highly competitive version of cumulative. Using decomposition into component parts automatically makes the propagator incremental and able to explain itself. We then show how, using the insights from the behaviour of the decomposition, we can create global cumulative constraints that explain their propagation. We compare these approaches to explaining the cumulative constraint on resourceconstrainedprojectschedulingproblems. All our methods are able to close a substantial number of open problems from the well-established PSPlib benchmark library of resource-constrained project scheduling problems.
This paper describes how the resource-constrained project scheduling problem (RCPSP) can be used as a basis for comprehensive disruption management, concerned with both rescheduling as well as potential structural pro...
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ISBN:
(纸本)9781424401956
This paper describes how the resource-constrained project scheduling problem (RCPSP) can be used as a basis for comprehensive disruption management, concerned with both rescheduling as well as potential structural process modifications. It is illustrated, how the RCPSP can be extended by the possibility to represent alternative activities and how the respective constructs can be used to describe various forms of typical interventions. Moreover, an approach for schedule optimization and the resolution of the generalized problem is presented, based on the combination of well-established methodologies and specific evolutionary operators. In an illustrative example it is finally shown how the proposed framework can be applied for the development of real-time decision support systems in the domain of airport ground process management.
In this paper, the Pre-emptive resource-constrainedprojectschedulingproject (PRCPSP) is considered. The paper mainly focuses on the problem 1_PRCPSP, where a maximum of one interruption per activity is allowed. A t...
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ISBN:
(纸本)9781424465866
In this paper, the Pre-emptive resource-constrainedprojectschedulingproject (PRCPSP) is considered. The paper mainly focuses on the problem 1_PRCPSP, where a maximum of one interruption per activity is allowed. A time-fragment linked-list method (TFLLM) is proposed to generate an effective solution for a given precedence-feasible activity list. Based on the TFLLM, an evolutionary algorithm is developed with the objective of makespan minimization. Computational experiments on the standard J30 and J60 sets show that the proposed algorithm can perform better than the compared approach in literature for the pre-emptive cases.
In this paper we consider a sports league schedulingproblem which occurs in planning non-professional table-tennis leagues. The problem consists in finding a schedule for a time-relaxed double round robin tournament ...
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In this paper we consider a sports league schedulingproblem which occurs in planning non-professional table-tennis leagues. The problem consists in finding a schedule for a time-relaxed double round robin tournament where different hard and soft constraints have to be taken into account. We model the problem as an integer linear program and a multi-mode resource-constrained project scheduling problem, respectively. Based on the second model a heuristic solution algorithm is proposed, which proceeds in two stages using local search and genetic algorithms. Computational results show the efficiency of the approaches. (C) 2009 Elsevier B.V. All rights reserved.
This paper presents the Local Search with Subproblem Exact Resolution (LSSPER) method based on large neighbourhood search for solving the resource-constrained project scheduling problem (RCPSP). At each step of the me...
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This paper presents the Local Search with Subproblem Exact Resolution (LSSPER) method based on large neighbourhood search for solving the resource-constrained project scheduling problem (RCPSP). At each step of the method, a subpart of the current solution is fixed while the other part defines a subproblem solved externally by a heuristic or an exact solution approach (using either constraint programming techniques or mathematical programming techniques). Hence, the method can be seen as a hybrid scheme. The key point of the method deals with the choice of the subproblem to be optimized. In this paper, we investigate the application of the method to the RCPSP. Several strategies for generating the subproblem are proposed. In order to evaluate these strategies, and, also, to compare the whole method with current state-of-the-art heuristics, extensive numerical experiments have been performed. The proposed method appears to be very efficient.
In this paper, we tackle the problem of scheduling multisite and multimode activities in order to minimise the project duration that meets the constraints imposed by limited resources. The industrial system is compose...
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In this paper, we tackle the problem of scheduling multisite and multimode activities in order to minimise the project duration that meets the constraints imposed by limited resources. The industrial system is composed of many production sites, and each site has its own resources called local resources, and every site can receive resources called global resources. The objective is to support the repartition of all the lots of pieces on different sites in a cooperative way, and to assign resources. The system reduced to only one site highlights the well-known problem of the Multimode resource-constrained project scheduling problem (MRCPSP). We propose a mathematical programming approach based on competitive feasible solutions and strong lower bounds, within quite reasonable computation times. The basic ingredients of this approach are the Lagrangean relaxation. We also propose a method based on stochastic descent with restart to compute large-sized industrial instances. The experiments show that this technique gives solutions close to the optimum. This seems to indicate that these resolution methods are good candidates for real industrial problems. [Received: 1 February 2007;Revised: 31 July 2007;Accepted: 31 October 2007]
resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the re...
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resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the projectscheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.
In this paper, we propose a hybrid genetic algorithm with fuzzy logic controller (flc-hGA) to solve the resource-constrained multiple projectschedulingproblem (rc-mPSP) which is well known NP-hard problem. Objective...
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In this paper, we propose a hybrid genetic algorithm with fuzzy logic controller (flc-hGA) to solve the resource-constrained multiple projectschedulingproblem (rc-mPSP) which is well known NP-hard problem. Objectives described in this paper are to minimize total project time and to minimize total tardiness penalty. However, it is difficult to treat the rc-mPSP problems with traditional optimization techniques. The proposed new approach is based on the design of genetic operators with fuzzy logic controller (FLC) through initializing the revised serial method which outperforms the non-preemptive scheduling with precedence and resources constraints. For these rc-mPSP problems, we demonstrate that the proposed flc-hGA yields better results than conventional genetic algorithms and adaptive genetic algorithm. (C) 2004 Elsevier B.V. All rights reserved.
resource-constrained project scheduling problem(RCPSP) is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities' cost with the r...
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resource-constrained project scheduling problem(RCPSP) is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities' cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the projectscheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.
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