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 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 A hybrid mathematical programming model and statistical approach for bidding price decision in construction projects

2021 ◽  
pp. 1-22 ◽  
Author(s):  
Hamid Rastegar ◽  
Behrouz Arbab Shirani ◽  
S. Hamid Mirmohammadi ◽  
Esmaeil Akhondi Bajegani
Keyword(s):  
Mathematical Model ◽  
Real World ◽  
Cost Estimation ◽  
Construction Projects ◽  
Programming Model ◽  
Uncertain Parameters ◽  
Estimation Errors ◽  
Price Decision ◽  
Bidding Price ◽  
The Cost

Bidding price decision is a key issue for the contractors and construction companies. The success/failure of the contractors in competitive biddings is directly dependent on their bidding strategy. This paper aims to develop a hybrid statistical and mathematical modeling approach for determining the optimum bidding price in construction projects. By statistical analysis of historical data, some uncertain parameters like the number of competitors and the cost of the project are estimated. Then, a scenario-based mathematical model for bidding price decision is proposed. In order to present a model in more accordance with the real-world situations, factors like risk, minimum acceptable rate of return (MARR) and opportunistic behavior are taken into account. In order to achieve an insensitive solution to the change in the realization of the input data from the scenarios, a robust mathematical model is used. The performance of the model is evaluated through some numerical problems. Furthermore, sensitivity analysis of the key parameters and robustness evaluation of the model against uncertain parameters are conducted. To evaluate the model's effectiveness in real-world situations, a case study is analyzed by the proposed approach. Numerical results show that the proposed approach reduces the cost estimation errors and increases the average expected profit, which validates the applicability of the model in a real-world situation.

scholarly journals MULTI-OBJECTIVE SYMBIOTIC ORGANISMS OPTIMIZATION FOR MAKING TIME-COST TRADEOFFS IN REPETITIVE PROJECT SCHEDULING PROBLEM

2019 ◽  
Vol 25 (4) ◽  
pp. 322-339 ◽  
Author(s):  
Duc-Hoc Tran ◽  
Jui-Sheng Chou ◽  
Duc-Long Luong
Keyword(s):  
Project Scheduling ◽  
Construction Projects ◽  
Time Cost ◽  
Symbiotic Organisms Search ◽  
Trade Off ◽  
Fundamental Limitations ◽  
Precedence Diagramming Method ◽  
Scheduling Method ◽  
The Cost ◽  
Symbiotic Organisms

Time-cost problems that arise in repetitive construction projects are commonly encountered in project scheduling. Numerous time-cost trade-off approaches, such as mathematical, metaheuristic, and evolutionary methods, have been extensively studied in the construction community. Currently, the scheduling of a repetitive project is conducted using the traditional precedence diagramming method (PDM), which has two fundamental limitations: (1) progress is assumed to be linear from start to finish; and (2) activities in the schedule are connected each other only at the end points. This paper proposes a scheduling method that allows the use of continuous precedence relationships and piece-wise linear and nonlinear activity-time-production functions that are described by the use of singularity functions. This work further develops an adaptive multiple objective symbiotic organisms search (AMOSOS) algorithm that modifies benefit factors in the basic SOS to balance exploration and exploitation processes. Two case studies of its application are analyzed to validate the scheduling method, as well as to demonstrate the capabilities of AMOSOS in generating solutions that optimally trade-off minimizing project time with minimizing the cost of non-unit repetitive projects. The results thus obtained indicate that the proposed model is feasible and effective relative to the basic SOS algorithm and other state-of-the-art algorithms.

scholarly journals A mixed integer linear programming model to support e-fulfillment strategies in warehouse-based supermarket chains

2021 ◽  
Author(s):  
Mar Vazquez-Noguerol ◽  
Jose A. Comesaña-Benavides ◽  
Sara Riveiro-Sanroman ◽  
J. Carlos Prado-Prado
Keyword(s):  
Mathematical Model ◽  
Linear Programming ◽  
Programming Model ◽  
Time Windows ◽  
Point Of View ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Maximum Efficiency ◽  
Online Sales ◽  
Delivery Times

AbstractThe use of the online channel has greatly increased the logistics costs of supermarket chains. Even the difficulty of managing order picking and delivery processes has increased due to the short delivery times and the preservation of perishable products. Against that backdrop, the proposed approach presents a mathematical model for planning the e-fulfillment activities with the objective of ensuring maximum efficiency. The linear programming model has been designed for e-grocers that prepare their online orders at central warehouses. The mathematical model determines both the time windows during which picking and transport should take place and the assignment of trucks to delivery routes. The allocation of online orders is performed taking into account the conservation requirement of each type of product and the availability of means. Considering this planning tool, managers can improve the decision-making process guaranteeing the quality of service while reducing the e-fulfillment cost for joint picking and delivery point of view. Motivated by a cooperation with a supermarket chain, results bring great insight based on the simulation of different logistics alternatives. Companies and researchers can compare the strategy of leveling the workload and the strategy of reducing the number of means, a common alternative in logistics outsourced to third parties. In addition, the different scenarios developed make it possible to determine the substantial savings achieved by modifying the delivery services and advancing the order preparation. As a result, managerial insights are identified highlighting the importance of efficient order planning to improve the profitability of online sales.

Mengurangi Durasi Pelaksanaan Proyek Dengan Menggunakan Metode Time Cost Trade Off

2021 ◽  
Vol 4 (2) ◽  
pp. 13
Author(s):  
Muhammad Rizal Hermawan ◽  
Ahmad Ridwan ◽  
Suwarno Suwarno
Keyword(s):  
Construction Projects ◽  
Method Development ◽  
Construction Project ◽  
Weather Conditions ◽  
Time Cost ◽  
Trade Off ◽  
Critical Pathways ◽  
Normal Duration ◽  
The Cost

Construction project management is one of the things that affect the smooth work of construction projects. Time and cost become benchmarks in the success of a project. In the construction project Bhayangkara Nganjuk hospital indicated experiencing delays caused by unse endorsive weather conditions. The delay will have an impact on the costs that will be incurred. The purpose of this research is to accelerate the time on the project by using the time cost trade off method. Development work includes IGD room work, Pharmaceutical Installation, Laboratory and Inpatiation Room. The data used in the form of Time schedule and budget plan costs obtained from the implementing contractor. From the data, analysis is carried out in the form of determination of relationships between jobs, determination of critical pathways, and acceleration analysis by applying a work shift system. The relationship between jobs is illustrated through the Microsoft Project. The results of the study obtained a total cost after acceleration of Rp. 3,873,505,632.00 the value was more expensive 11.25% than the normal cost of the project of Rp 3,481,698,000.00. With an accelerated duration of 125 days or 25.71% faster than the normal duration of the project of 180 days. So that from these results, it can be used as a reference in the implementation of the project regarding work hours that can be applied as well as the cost of the project and the duration of acceleration required.

scholarly journals New general mixed-integer linear programming model for mobile workforce management

2021 ◽  
Author(s):  
András Éles ◽  
István Heckl ◽  
Heriberto Cabezas
Keyword(s):  
Programming Model ◽  
Time Windows ◽  
Mutual Exclusion ◽  
Parallel Execution ◽  
Mixed Integer ◽  
Management Problem ◽  
Routing Problem ◽  
Workforce Management ◽  
Computational Performance ◽  
Wide Range

AbstractA mathematical model is introduced to solve a mobile workforce management problem. In such a problem there are a number of tasks to be executed at different locations by various teams. For example, when an electricity utility company has to deal with planned system upgrades and damages caused by storms. The aim is to determine the schedule of the teams in such a way that the overall cost is minimal. The mobile workforce management problem involves scheduling. The following questions should be answered: when to perform a task, how to route vehicles—the vehicle routing problem—and the order the sites should be visited and by which teams. These problems are already complex in themselves. This paper proposes an integrated mathematical programming model formulation, which, by the assignment of its binary variables, can be easily included in heuristic algorithmic frameworks. In the problem specification, a wide range of parameters can be set. This includes absolute and expected time windows for tasks, packing and unpacking in case of team movement, resource utilization, relations between tasks such as precedence, mutual exclusion or parallel execution, and team-dependent travelling and execution times and costs. To make the model able to solve larger problems, an algorithmic framework is also implemented which can be used to find heuristic solutions in acceptable time. This latter solution method can be used as an alternative. Computational performance is examined through a series of test cases in which the most important factors are scaled.

scholarly journals An Optimized Mathematical Model for Items Supplies Planning of a Logistic System

2016 ◽  
Vol 10 (10) ◽  
pp. 133
Author(s):  
Mohammad Ali Nasiri Khalili ◽  
Mostafa Kafaei Razavi ◽  
Morteza Kafaee Razavi
Keyword(s):  
Mathematical Model ◽  
Mixed Integer ◽  
Logistics System ◽  
Proposed Model ◽  
Multiple Objective Decision Making ◽  
System Requirements ◽  
Purchasing Logistics ◽  
The Cost ◽  
The Mathematical Model ◽  
First Time

Items supplies planning of a logistic system is one of the major issue in operations research. In this article the aim is to determine how much of each item per month from each supplier logistics system requirements must be provided. To do this, a novel multi objective mixed integer programming mathematical model is offered for the first time. Since in logistics system, delivery on time is very important, the first objective is minimization of time in delivery on time costs (including lack and maintenance costs) and the cost of purchasing logistics system. The second objective function is minimization of the transportation supplier costs. Solving the mathematical model shows how to use the Multiple Objective Decision Making (MODM) can provide the ensuring policy and transportation logistics needed items. This model is solved with CPLEX and computational results show the effectiveness of the proposed model.

scholarly journals Minimising negative externalities cost using 0-1 mixed integer linear programming model in e-commerce environment

2017 ◽  
Vol 11 ◽  
Author(s):  
Akyene Tetteh ◽  
Sarah Dsane-Nsor
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Petroleum Products ◽  
Mixed Integer ◽  
The Internet ◽  
Negative Externalities ◽  
The Government ◽  
The Cost

Background: Although the Internet boosts business profitability, without certain activities like efficient transportation, scheduling, products ordered via the Internet may reach their destination very late. The environmental problems (vehicle part disposal, carbon monoxide [CO], nitrogen oxide [NOx] and hydrocarbons [HC]) associated with transportation are mostly not accounted for by industries.Objectives: The main objective of this article is to minimising negative externalities cost in e-commerce environments.Method: The 0-1 mixed integer linear programming (0-1 MILP) model was used to model the problem statement. The result was further analysed using the externality percentage impact factor (EPIF).Results: The simulation results suggest that (1) The mode of ordering refined petroleum products does not impact on the cost of distribution, (2) an increase in private cost is directly proportional to the externality cost, (3) externality cost is largely controlled by the government and number of vehicles used in the distribution and this is in no way influenced by the mode of request (i.e. Internet or otherwise) and (4) externality cost may be reduce by using more ecofriendly fuel system.

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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