In order to minimize the project duration of resourceconstrained project scheduling problem( RCPSP), a gene expression programming-based scheduling rule( GEP-SR) method is proposed to automatically discover and select...In order to minimize the project duration of resourceconstrained project scheduling problem( RCPSP), a gene expression programming-based scheduling rule( GEP-SR) method is proposed to automatically discover and select the effective scheduling rules( SRs) which are constructed using the project status and attributes of the activities. SRs are represented by the chromosomes of GEP, and an improved parallel schedule generation scheme( IPSGS) is used to transform the SRs into explicit schedules. The framework of GEP-SR for RCPSP is designed,and the effectiveness of the GEP-SR approach is demonstrated by comparing with other methods on the same instances.展开更多
The resource constrained project scheduling problem (RCPSP) and a decision-making model based on multi-agent systems (MAS) and general equilibrium marketing are proposed. An algorithm leading to the resource allocatio...The resource constrained project scheduling problem (RCPSP) and a decision-making model based on multi-agent systems (MAS) and general equilibrium marketing are proposed. An algorithm leading to the resource allocation decision involved in RCPSP has also been developed. And this algorithm can be used in the multi-project scheduling field as well.Finally, an illustration is given.展开更多
This paper presents a new method to solve the resource-constrained project scheduling problem for software development. In this method,activity duration times are described as fuzzy variables and resource-constrained ...This paper presents a new method to solve the resource-constrained project scheduling problem for software development. In this method,activity duration times are described as fuzzy variables and resource-constrained software project scheduling problems are described as fuzzy programming models. First,how to model the software project scheduling problem under the fuzzy environment conditions is proposed. Second,in order to satisfy the different requirements of decision-making,two novel fuzzy project scheduling models,expected cost model and credibility maximization model,are suggested. Third,a hybrid intelligent algorithm integrated by genetic algorithm and fuzzy simulation is designed to solve the above two fuzzy programming models. Numerical experiments illustrate the effectiveness of the hybrid intelligent algorithm.展开更多
To solve the resource-constrained multiple project scheduling problem(RCMPSP) more effectively,a method based on timed colored Petri net(TCPN) was proposed.In this methodology,firstly a novel mapping mechanism between...To solve the resource-constrained multiple project scheduling problem(RCMPSP) more effectively,a method based on timed colored Petri net(TCPN) was proposed.In this methodology,firstly a novel mapping mechanism between traditional network diagram such as CPM(critical path method)/PERT(program evaluation and review technique) and TCPN was presented.Then a primary TCPN(PTCPN) for solving RCMPSP was modeled based on the proposed mapping mechanism.Meanwhile,the object PTCPN was used to simulate the multiple projects scheduling and to find the approximately optimal value of RCMPSP.Finally,the performance of the proposed approach for solving RCMPSP was validated by executing a mould manufacturing example.展开更多
This study utilizes a time-precedence network technique to construct two models of multi-mode resource constrained project scheduling problem with discounted cash flows （MRCPSPDCF）, individually including the progre...This study utilizes a time-precedence network technique to construct two models of multi-mode resource constrained project scheduling problem with discounted cash flows （MRCPSPDCF）, individually including the progress payment （PP） and the payment at an equal time interval （ETI）. The objective of each model is to maximize the net present value （NPV） for all cash flows in the project, subject to the related operational constraints. The models are characterized as NP-hard. A heuristic algorithm, coupled with two upper bound solutions, is proposed to efficiently solve the models and evaluate the heuristic algorithm performance which was not performed in past studies. The results show that the performance of proposed models and heuristic algorithm is good.展开更多
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...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 project scheduling. 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.展开更多
In supply chain management (SCM) environment, we consider a resource-constrained project scheduling problem (rcPSP) model as one of advanced scheduling problems considered by a constraint programming technique. We de...In supply chain management (SCM) environment, we consider a resource-constrained project scheduling problem (rcPSP) model as one of advanced scheduling problems considered by a constraint programming technique. We develop a hybrid genetic algorithm (hGA) with a fuzzy logic controller (FLC) to solve the rcPSP which is the well known NP-hard problem. This new approach is based on the design of genetic operators with FLC through initializing the serial method which is superior for a large rcPSP scale. For solving these rcPSP problems, we first demonstrate that our hGA with FLC (flc-hGA) yields better results than several heuristic procedures presented in the literature. We have revealed a fact that flc-hGA has the evolutionary behaviors of average fitness better than hGA without FLC.展开更多
In this study,we considered a bi-objective,multi-project,multi-mode resource-constrained project scheduling problem.We adopted three objective pairs as combinations of the net present value(NPV)as a financial performa...In this study,we considered a bi-objective,multi-project,multi-mode resource-constrained project scheduling problem.We adopted three objective pairs as combinations of the net present value(NPV)as a financial performance measure with one of the time-based performance measures,namely,makespan(Cmax),mean completion time(MCT),and mean flow time(MFT)(i.e.,minCmax/maxA^PF,minA/Cr/max7VPF,and min MFTI mdixNPV).We developed a hybrid non-dominated sorting genetic algorithm Ⅱ(hybrid-NSGA-Ⅱ)as a solution method by introducing a backward-forward pass(BFP)procedure and an injection procedure into NSGA-Ⅱ.The BFP was proposed for new population generation and post-processing.Then,an injection procedure was introduced to increase diversity.The BFP and injection procedures led to improved objective functional values.The injection procedure generated a significantly high number of non-dominated solutions,thereby resulting in great diversity.An extensive computational study was performed.Results showed that hybrid-NSGA-Ⅱ surpassed NSGA-Ⅱ in terms of the performance metrics hypervolume,maximum spread,and the number of nondominated solutions.Solutions were obtained for the objective pairs using hybrid-NSGA-Ⅱ and three different test problem sets with specific properties.Further analysis was performed by employing cash balance,which was another financial performance measure of practical importance.Several managerial insights and extensions for further research were presented.展开更多
This paper deals with the problem of project scheduling subject to multiple execution modes with non-renewable resources, and a model that handles some of monetary issues in real world applications.The objective is to...This paper deals with the problem of project scheduling subject to multiple execution modes with non-renewable resources, and a model that handles some of monetary issues in real world applications.The objective is to schedule the activities to maximize the expected net present value(NPV) of the project, taking into account the activity costs, the activity durations, and the cash flows generated by successfully completing an activity.Owing to the combinatorial nature of this problem, the current study develops a hybrid of branch-and-bound procedure and memetic algorithm to enhance both mode assignment and activity scheduling.Modifications for the makespan minimization problem have been made through a set of benchmark problem instances.Algorithmic performance is rated on the maximization of the project NPV and computational results show that the two-phase hybrid metaheuristic performs competitively for all instances of different problem sizes.展开更多
基金The Spring Plan of Ministry of Education,China(No.Z2012017)
文摘In order to minimize the project duration of resourceconstrained project scheduling problem( RCPSP), a gene expression programming-based scheduling rule( GEP-SR) method is proposed to automatically discover and select the effective scheduling rules( SRs) which are constructed using the project status and attributes of the activities. SRs are represented by the chromosomes of GEP, and an improved parallel schedule generation scheme( IPSGS) is used to transform the SRs into explicit schedules. The framework of GEP-SR for RCPSP is designed,and the effectiveness of the GEP-SR approach is demonstrated by comparing with other methods on the same instances.
文摘The resource constrained project scheduling problem (RCPSP) and a decision-making model based on multi-agent systems (MAS) and general equilibrium marketing are proposed. An algorithm leading to the resource allocation decision involved in RCPSP has also been developed. And this algorithm can be used in the multi-project scheduling field as well.Finally, an illustration is given.
基金Supported by the National Natural Science Foundation of China (60975050)the Specialized Research Fund for the Doctoral Program of Higher Education of China (20070486081)
文摘This paper presents a new method to solve the resource-constrained project scheduling problem for software development. In this method,activity duration times are described as fuzzy variables and resource-constrained software project scheduling problems are described as fuzzy programming models. First,how to model the software project scheduling problem under the fuzzy environment conditions is proposed. Second,in order to satisfy the different requirements of decision-making,two novel fuzzy project scheduling models,expected cost model and credibility maximization model,are suggested. Third,a hybrid intelligent algorithm integrated by genetic algorithm and fuzzy simulation is designed to solve the above two fuzzy programming models. Numerical experiments illustrate the effectiveness of the hybrid intelligent algorithm.
文摘To solve the resource-constrained multiple project scheduling problem(RCMPSP) more effectively,a method based on timed colored Petri net(TCPN) was proposed.In this methodology,firstly a novel mapping mechanism between traditional network diagram such as CPM(critical path method)/PERT(program evaluation and review technique) and TCPN was presented.Then a primary TCPN(PTCPN) for solving RCMPSP was modeled based on the proposed mapping mechanism.Meanwhile,the object PTCPN was used to simulate the multiple projects scheduling and to find the approximately optimal value of RCMPSP.Finally,the performance of the proposed approach for solving RCMPSP was validated by executing a mould manufacturing example.
文摘This study utilizes a time-precedence network technique to construct two models of multi-mode resource constrained project scheduling problem with discounted cash flows （MRCPSPDCF）, individually including the progress payment （PP） and the payment at an equal time interval （ETI）. The objective of each model is to maximize the net present value （NPV） for all cash flows in the project, subject to the related operational constraints. The models are characterized as NP-hard. A heuristic algorithm, coupled with two upper bound solutions, is proposed to efficiently solve the models and evaluate the heuristic algorithm performance which was not performed in past studies. The results show that the performance of proposed models and heuristic algorithm is good.
文摘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 project scheduling. 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.
文摘In supply chain management (SCM) environment, we consider a resource-constrained project scheduling problem (rcPSP) model as one of advanced scheduling problems considered by a constraint programming technique. We develop a hybrid genetic algorithm (hGA) with a fuzzy logic controller (FLC) to solve the rcPSP which is the well known NP-hard problem. This new approach is based on the design of genetic operators with FLC through initializing the serial method which is superior for a large rcPSP scale. For solving these rcPSP problems, we first demonstrate that our hGA with FLC (flc-hGA) yields better results than several heuristic procedures presented in the literature. We have revealed a fact that flc-hGA has the evolutionary behaviors of average fitness better than hGA without FLC.
文摘In this study,we considered a bi-objective,multi-project,multi-mode resource-constrained project scheduling problem.We adopted three objective pairs as combinations of the net present value(NPV)as a financial performance measure with one of the time-based performance measures,namely,makespan(Cmax),mean completion time(MCT),and mean flow time(MFT)(i.e.,minCmax/maxA^PF,minA/Cr/max7VPF,and min MFTI mdixNPV).We developed a hybrid non-dominated sorting genetic algorithm Ⅱ(hybrid-NSGA-Ⅱ)as a solution method by introducing a backward-forward pass(BFP)procedure and an injection procedure into NSGA-Ⅱ.The BFP was proposed for new population generation and post-processing.Then,an injection procedure was introduced to increase diversity.The BFP and injection procedures led to improved objective functional values.The injection procedure generated a significantly high number of non-dominated solutions,thereby resulting in great diversity.An extensive computational study was performed.Results showed that hybrid-NSGA-Ⅱ surpassed NSGA-Ⅱ in terms of the performance metrics hypervolume,maximum spread,and the number of nondominated solutions.Solutions were obtained for the objective pairs using hybrid-NSGA-Ⅱ and three different test problem sets with specific properties.Further analysis was performed by employing cash balance,which was another financial performance measure of practical importance.Several managerial insights and extensions for further research were presented.
文摘This paper deals with the problem of project scheduling subject to multiple execution modes with non-renewable resources, and a model that handles some of monetary issues in real world applications.The objective is to schedule the activities to maximize the expected net present value(NPV) of the project, taking into account the activity costs, the activity durations, and the cash flows generated by successfully completing an activity.Owing to the combinatorial nature of this problem, the current study develops a hybrid of branch-and-bound procedure and memetic algorithm to enhance both mode assignment and activity scheduling.Modifications for the makespan minimization problem have been made through a set of benchmark problem instances.Algorithmic performance is rated on the maximization of the project NPV and computational results show that the two-phase hybrid metaheuristic performs competitively for all instances of different problem sizes.
