In this paper a meta heuristic Particle Swarm Optimization (PSO)-based approach for the solution of the resource-constrained project scheduling problem with the purpose of minimizing project time has been developed. I...
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ISBN:
(纸本)9788132210405
In this paper a meta heuristic Particle Swarm Optimization (PSO)-based approach for the solution of the resource-constrained project scheduling problem with the purpose of minimizing project time has been developed. In order to evaluate the performance of the PSO based approach for the resource-constrained project scheduling problem, computational analyses are given. As per the results the application of PSO to projectscheduling is achievable.
The paper presents a formal description of the resource allocation problem for resource-constrained project scheduling. A schedule can be executed by various resource flow networks which may differ in terms of resista...
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The paper presents a formal description of the resource allocation problem for resource-constrained project scheduling. A schedule can be executed by various resource flow networks which may differ in terms of resistance to disruptions occurring during project execution. The authors define such criteria of evaluating a resource flow network which can be more useful than robustness metrics used so far in the research. The authors discuss the importance of robust scheduling for execution projects and propose metrics for resource allocation robustness which take into consideration the stability of the final schedule. Those metrics make it possible to carry out a more precise analysis concerning the properties of the resource flow network in terms of its robustness to disruptions in comparison with a well known flexibility indicator, flex.
Harris hawks optimization (HHO) is one of the leading optimization approaches due to its efficacy and multi-choice structure with time-varying components. The HHO has been applied in various areas due to its simplicit...
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Harris hawks optimization (HHO) is one of the leading optimization approaches due to its efficacy and multi-choice structure with time-varying components. The HHO has been applied in various areas due to its simplicity and outstanding performance. However,the original HHO can be improved and evolved in terms of convergence trends, and it is prone to local optimization under certain circumstances. Therefore, the performance and robustness of the algorithm need to be further improved. In our research, based on the core principle of evolutionary methods, we first developed an elite evolutionary strategy (EES) and then utilized it to advance HHO's convergence speed and ability to jump out of the local optimum. We named such an enhanced hybrid algorithm EESHHO in this paper. To verify the effectiveness and robustness of the EESHHO, we tested it on 29 numerical optimization test functions, including 23 classic basic test functions and 6 composite test functions from the IEEE CEC2017 special session. Moreover, we apply the EESHHO on resource-constrained project scheduling and QoS-aware web service composition problems to further validate the effectiveness of EESHHO. The experimental results show that proposed EESHHO has faster convergence speed and better optimization performance by comparing it with other mainstream algorithms.
This paper addresses the multi-objective resource-constrained project scheduling problems with stochastic activity durations and alternative execution methods. Three objectives are considered: minimizing expected make...
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This paper addresses the multi-objective resource-constrained project scheduling problems with stochastic activity durations and alternative execution methods. Three objectives are considered: minimizing expected makespan, expected cost and robustness. Chance constrained programming is applied for formulating this stochastic problem. A hybrid approach that integrates sample average approximation (SAA) and an improved multi-objective chaotic quantum-behaved particle swarm optimization (MOCQPSO) algorithm is proposed. To improve the diversity of solutions and enhance the global search ability, a two-stage learning strategy that balances the exploration and the exploitation is proposed for MOCQPSO. In addition, chaotic operators including chaotic initialization, crossover and mutation are also introduced. Six benchmark functions and an instance generator based on the RCPSP dataset of PSPLIB are designed to validate the performance of the proposed algorithm. The experimental results demonstrate that our proposed method outperforms the original algorithms in solution diversity and quality.
This paper reviews compact continuous-time formulations for the multi-mode resource-constrained project scheduling problem. Specifically, we first point out a serious flaw in an existing start-end-event-based formulat...
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This paper reviews compact continuous-time formulations for the multi-mode resource-constrained project scheduling problem. Specifically, we first point out a serious flaw in an existing start-end-event-based formulation owing to inconsistent mode choices. We propose two options to formulate the missing constraints and consider an equivalent reformulation with sparser constraint matrix. Second, we formulate an aggregate variant of an existing model that relies on on-off-events, and we clarify the role of mode consistency issues in such models. Third, we suggest two variants of an existing network flow formulation. We enhance our models by adapting several techniques that have been used previously, e.g., in cases with only a single mode. A large set of benchmark instances from the literature provides the basis for an up-to-date and fair computational study with an out-of-the-box solver package. We compare our models against two models from the literature. Our experiments assert confidently that network flow formulations prevail in the test bed, and they provide a hint on why event-based models become less competitive in multi-mode settings.
Critical chain scheduling/Buffer management (CCS/BM)—the direct application of the theory of constraints (TOC) to project management—has received much attention in project management literature. There still is contr...
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Critical chain scheduling/Buffer management (CCS/BM)—the direct application of the theory of constraints (TOC) to project management—has received much attention in project management literature. There still is controversy over the merits and pitfalls of the CCS/BM methodology. This paper focuses on the fundamental elements of CCS/BM logic and pinpoints some intricacies that are not commonly referred to in the available literature. The authors’ analysis is based on a critical review of the relevant sources and experimentation with both commercial CCS/BM software and an internally developed CCS/BM-based tool.
The article presents the resource-constrained project scheduling problem with the maximisation of discounted cash flows from the contractor's perspective: with cash outflows related to starting individual activiti...
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The article presents the resource-constrained project scheduling problem with the maximisation of discounted cash flows from the contractor's perspective: with cash outflows related to starting individual activities and with cash inflows for completing project stages (milestones). The authors propose algorithms for improving a forward active schedule by iterative one-unit right shifts of activities, taking into account different resource flow networks. To illustrate the algorithms and problem, a numerical example is presented. Finally, the algorithms are tested using standard test problems with additionally defined cash flows and contractual milestones.
In practice, multi-skilled labor is widely used. There are constraints of available and unavailable time on those resources, and each resource possesses multiple different skills. For the resource attributes of multip...
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ISBN:
(纸本)9781479937066
In practice, multi-skilled labor is widely used. There are constraints of available and unavailable time on those resources, and each resource possesses multiple different skills. For the resource attributes of multiple skills and time windows, it's extremely challenging to arrange the activities and allocate resources in projectscheduling. Aimed at this kind of problems, a mathematic programming model is developed and a Rollout Algorithm based on priority rules is proposed. In order to allocate resources quickly;a heuristic method for resource allocation is embedded in the algorithm. The results of some numerical experiments indicate that the performance of the proposed algorithm could obtain the satisfactory solution of the problem and be suitable for solving the problems of large scale. It is velified that the algorithm is effective.
We study an assignment type resource-con- strained projectscheduling problem with resources being multi-skilled personnel to minimize the total staffing costs. We develop a hybrid Benders decomposition (HBD) algorith...
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We study an assignment type resource-con- strained projectscheduling problem with resources being multi-skilled personnel to minimize the total staffing costs. We develop a hybrid Benders decomposition (HBD) algorithm that combines the complimentary strengths of both mixed-integer linear programming (MILP) and constraint programming (CP) to solve this NP-hard optimization problem. An effective cut-generating scheme based on temporal analysis in projectscheduling is devised for resolving resource conflicts. The computational study shows that our hybrid MILP/CP algorithm is both effective and efficient compared to the pure MILP or CP method alone.
Activity overlapping in project management and concurrent engineering allows a downstream activity to start before the end of its upstream activity based on some preliminary information and feedback. Because the preli...
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Activity overlapping in project management and concurrent engineering allows a downstream activity to start before the end of its upstream activity based on some preliminary information and feedback. Because the preliminary information can be issued at multiple stages during an upstream activity's execution, the downstream activity may have multiple overlapping modes. projectscheduling with activity overlapping has a wide range of applications in manufacturing, R&D, construction and professional service industries. An optimal overlapping plan may help project manager accelerate project progress effectively with improved rate of investment. In this research, we study a resource-constrained project scheduling problem with multiple overlapping modes, which is NP-hard. To obtain high-quality near-optimal solutions, we formulate it as a dynamic program (DP), and develop a rollout policy based approximate dynamic programming (ADP) algorithm to obtain near-optimal policy efficiently. Our rollout policy sequentially improves over a priority-rule base policy. A rollout procedure based on pre-processing of overlapping options is also devised which we call pre-rollout. The pre-rollout improves over the rollout in some instances with moderately more computational time. A comprehensive experiment is performed on the PSPLIB benchmark instances. Computational results show that our rollout policy and the pre-rollout procedure significantly outperform the exact integer linear programming (ILP) solutions in both solution quality and computational time for medium and large instances.
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