Abstract. 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.
Abstract. The paper presents the resource-constrained project scheduling with cash flow optimisation. New project models with bonuspenalty system and payoff in stages have been proposed. For the models presented, the application of proactive scheduling is analysed, as designed to improve project execution under uncertainty. Next, schedule robustness is discussed and measures of robustness are proposed.
Abstract. The paper analyses the problem of discounted cash flow maximising for the resource-constrained project scheduling from the project contractor's perspective. Financial optimisation for the multi-stage project is considered. Cash outflows are the contactor's expenses related to activity execution. Cash inflows are the client's payments for the completed milestones. To solve the problem, the procedure of backward scheduling taking into account contractual milestones is proposed. The effectiveness of this procedure, as used to generate solutions for the simulated annealing algorithm, is verified with use of standard test instances with additionally defined cash flows and contractual milestones.
Abstract. 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.
Abstract. This paper presents a Resource-Constrained Project Scheduling Problem (RCPSP) settled by contractual milestones. The criterion analysed here is the maximisation of aggregate discounted cash flows from the contractor's perspective, known as an RCPSP problem with Discounted Cash Flows (RCPSPDCF). The cash flows analysed here cover the contractor's cash outflows (negative cash flows), related to the commencement of individual activities, and cash inflows (positive cash flows) after the fulfilment of individual milestones. The authors propose a two-phase algorithm for solving the problem defined. In the first phase, the simulated annealing metaheuristics is used, designed to identify a forward schedule with as high total DCF as possible. In the second phase, the best first-phase schedule is improved by right shifts of activities. To this end, the procedure which iteratively shifts tasks by one unit is applied, with a view to maximising the objective function. Activity shifts take into consideration precedence and resource constraints, and they are performed for a specified resource allocation to activities. This paper also includes an analysis of the problem for a sample project. The results of computational experiments are then analysed. The experiments were run with the use of standard test problems from the Project Scheduling Problem LIBrary (PSPLIB), with additionally defined cash flows and contractual milestones.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.