scholarly journals Robust Proactive Project Scheduling Model for the Stochastic Discrete Time/Cost Trade-Off Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Hongbo Li ◽  
Zhe Xu ◽  
Li Xiong ◽  
Yinbin Liu
Keyword(s):  
Discrete Time ◽  
Project Scheduling ◽  
Programming Model ◽  
Optimization Theory ◽  
Mixed Integer ◽  
Time Cost ◽  
Activity Time ◽  
Interval Numbers ◽  
Trade Off ◽  
Scheduling Model

We study the project budget version of the stochastic discrete time/cost trade-off problem (SDTCTP-B) from the viewpoint of the robustness in the scheduling. Given the project budget and a set of activity execution modes, each with uncertain activity time and cost, the objective of the SDTCTP-B is to minimize the expected project makespan by determining each activity’s mode and starting time. By modeling the activity time and cost using interval numbers, we propose a proactive project scheduling model for the SDTCTP-B based on robust optimization theory. Our model can generate robust baseline schedules that enable a freely adjustable level of robustness. We convert our model into its robust counterpart using a form of the mixed-integer programming model. Extensive experiments are performed on a large number of randomly generated networks to validate our model. Moreover, simulation is used to investigate the trade-off between the advantages and the disadvantages of our robust proactive project scheduling model.

scholarly journals Model of Construction Subcontractors Selection with Time Windows for their Availability

2019 ◽  
Vol 65 (4) ◽  
pp. 295-307
Author(s):  
S. Biruk ◽  
P. Jaskowski ◽  
M. Krzemiński
Keyword(s):  
Mathematical Model ◽  
Resource Availability ◽  
Construction Projects ◽  
Programming Model ◽  
Time Windows ◽  
Mixed Integer ◽  
Time Cost ◽  
Trade Off ◽  
Availability Constraints ◽  
The Cost

AbstractMost construction projects involve subcontracting some work packages. A subcontractor is employed on the basis of their bid as well as according to their availability. A viable schedule must account for resource availability constraints. These resources (e.g. crews, subcontractors) engage in many projects, so they become at the disposal for a new project only in certain periods. One of the key tasks of a planner is thus synchronizing the work of resources between concurrent projects. The paper presents a mathematical model of the problem of selecting subcontractors or general contractor’s crews for a time-constrained project that accounts for the availability of contractors, as well as for the cost of subcontracting works. The proposed mixed integer-binary linear programming model enables the user to perform the time/cost trade-off analysis.

scholarly journals New Computational Results on the Discrete Time/Cost Trade-Off Problem in Project Networks

1998 ◽  
Vol 49 (11) ◽  
pp. 1153 ◽  
Author(s):  
E. Demeulemeester ◽  
B. De Reyck ◽  
B. Foubert ◽  
W. Herroelen ◽  
M. Vanhoucke
Keyword(s):  
Discrete Time ◽  
Computational Results ◽  
Time Cost ◽  
Trade Off ◽  
Project Networks

The discrete time/cost trade-off problem: extensions and heuristic procedures

2007 ◽  
Vol 10 (4-5) ◽  
pp. 311-326 ◽  
Author(s):  
Mario Vanhoucke ◽  
Dieter Debels
Keyword(s):  
Discrete Time ◽  
Time Cost ◽  
Trade Off ◽  
Heuristic Procedures

Multicriteria Synthesis of Trigeneration Systems Assisted With Renewable Energy Sources and Thermal Energy Storage

2017 ◽  
Author(s):  
Eduardo A. Pina ◽  
Miguel A. Lozano ◽  
Luis M. Serra
Keyword(s):  
Co2 Emissions ◽  
Energy Demand ◽  
High Efficiency ◽  
Programming Model ◽  
Environmental Concern ◽  
Renewable Energy Sources ◽  
Mixed Integer ◽  
Total Annual Cost ◽  
Trade Off ◽  
Conflicting Objectives

The increasing world energy demand as a result of society development brings forth a growing environmental concern. The use of high-efficiency alternative systems is becoming progressively more interesting due to economic reasons and regional incentives. The issue of finding the best configuration that minimizes total annual cost is not enough anymore, as the environmental concern has become one of the objectives in the synthesis of energy systems. The minimization of costs is often contradictory to the minimization of environmental impact. Multi-objective optimization tackles the conflicting objectives issue by providing a set of trade-off solutions, or Pareto solutions, that can be examined by the decision maker in order to choose the best configuration for the given scenario. The present work proposes a mixed integer linear programming model for the synthesis of a trigeneration system that must attend the electricity, heat, and cooling demands of a multifamily building complex in Zaragoza, Spain. The objective functions to be minimized are the overall annual costs and the overall annual CO2 emissions, considering investment, maintenance and operation costs. As a first approach, the single-objective configurations for each objective function are evaluated. Then, the Pareto frontier is obtained for the minimization of total annual costs and total annual CO2 emissions, allowing to obtain the best trade-off configuration, which brings results close to the optimal single objectives. It is worth mentioning that the treatment of the energy prices was simplified in order to keep on the same level of detail as energy CO2 emissions, which are given only on an annual basis. On the other hand, the optimization model developed can be further complicated in order to consider more complex situations.

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