Developing Schedule With Linear Programming (Case Study: STTF II Project Komplek Sukamukti Banjaran)

2020 ◽  
Vol 4 (02) ◽  
pp. 34-45
Author(s):  
Naufal Dzikri Afifi ◽  
Ika Arum Puspita ◽  
Mohammad Deni Akbar
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Project Scheduling ◽  
Time Limit ◽  
Minimum Time ◽  
Service Cost ◽  
Trade Off ◽  
Overtime Work ◽  
The Cost

Shift to The Front II Komplek Sukamukti Banjaran Project is one of the projects implemented by one of the companies engaged in telecommunications. In its implementation, each project including Shift to The Front II Komplek Sukamukti Banjaran has a time limit specified in the contract. Project scheduling is an important role in predicting both the cost and time in a project. Every project should be able to complete the project before or just in the time specified in the contract. Delay in a project can be anticipated by accelerating the duration of completion by using the crashing method with the application of linear programming. Linear programming will help iteration in the calculation of crashing because if linear programming not used, iteration will be repeated. The objective function in this scheduling is to minimize the cost. This study aims to find a trade-off between the costs and the minimum time expected to complete this project. The acceleration of the duration of this study was carried out using the addition of 4 hours of overtime work, 3 hours of overtime work, 2 hours of overtime work, and 1 hour of overtime work. The normal time for this project is 35 days with a service fee of Rp. 52,335,690. From the results of the crashing analysis, the alternative chosen is to add 1 hour of overtime to 34 days with a total service cost of Rp. 52,375,492. This acceleration will affect the entire project because there are 33 different locations worked on Shift to The Front II and if all these locations can be accelerated then the duration of completion of the entire project will be effective

MINIMIZING THE COMPLETE INFLUENCE TIME IN A SOCIAL NETWORK WITH STOCHASTIC COSTS FOR INFLUENCING NODES

2013 ◽  
Vol 21 (supp01) ◽  
pp. 63-74 ◽  
Author(s):  
YAODONG NI ◽  
QIAONI SHI
Keyword(s):  
Social Network ◽  
Computational Complexity ◽  
Stochastic Programming ◽  
Greedy Algorithm ◽  
Random Graphs ◽  
Minimum Time ◽  
Programming Models ◽  
Decision Criteria ◽  
Trade Off ◽  
The Cost

In this paper, we study the problem of targeting a set of individuals to trigger a cascade of influence in a social network such that the influence diffuses to all individuals with the minimum time, given that the cost of initially influencing each individual is with randomness and that the budget available is limited. We adopt the incremental chance model to characterize the diffusion of influence, and propose three stochastic programming models that correspond to three different decision criteria respectively. A modified greedy algorithm is presented to solve the proposed models, which can flexibly trade off between solution performance and computational complexity. Experiments are performed on random graphs, by which we show that the algorithm we present is effective.

TODA

2018 ◽  
Vol 10 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Cida Sanches ◽  
Samuel Ferreira Jr ◽  
Givaldo Santos ◽  
Marisa Regina Paixão ◽  
Manuel Meireles
Keyword(s):  
Decision Analysis ◽  
Objective Function ◽  
Analysis Method ◽  
Case Study Method ◽  
Application Process ◽  
Ahp Method ◽  
Trade Off ◽  
Software Application

This paper describes the use and application of the TODA (Trade-off Decision Analysis) method through a case study. The method uses the concept of trade-off applied to a prioritization matrix and, to define the weights, it takes the concept of causality into account. Studies have shown that the TODA achieves the same results as the competing AHP method. However, it is easier to operate. The methodology used is a case study concerning the choice of the type of car for a fleet of vehicles to be driven by salespeople. Together with the software application process, the methods that aided the weighting of the criteria are described and how the values of the alternatives are converted into coefficients of the objective function. The results clearly show that the method is easily applied, but the limitations of the case study method preclude forming generalizations.

scholarly journals Cost Optimal Project Scheduling

Organizacija ◽  
2008 ◽  
Vol 41 (4) ◽  
pp. 153-158
Author(s):  
Uroš Klanšek ◽  
Mirko Pšunder
Keyword(s):  
Nonlinear Programming ◽  
Objective Function ◽  
Project Scheduling ◽  
Programming Approach ◽  
Project Duration ◽  
Numerical Example ◽  
Activity Duration ◽  
The Cost ◽  
Total Project Cost ◽  
Total Project

Cost Optimal Project SchedulingThis paper presents the cost optimal project scheduling. The optimization was performed by the nonlinear programming approach, NLP. The nonlinear total project cost objective function is subjected to the rigorous system of the activity precedence relationship constraints, the activity duration constraints and the project duration constraints. The set of activity precedence relationship constraints was defined to comprise Finish-to-Start, Start-to-Start, Start-to-Finish and Finish-to-Finish precedence relationships between activities. The activity duration constraints determine relationships between minimum, maximum and possible duration of the project activities. The project duration constraints define the maximum feasible project duration. A numerical example is presented at the end of the paper in order to present the applicability of the proposed approach.

scholarly journals Kajian Pengaruh Percepatan Waktu Pekerjaan Konstruksi Terhadap Biaya Proyek Bess Mansion Apartement Surabaya

2019 ◽  
Vol 2 (2) ◽  
pp. 69
Author(s):  
Adi Aprian Jaya ◽  
Kusnul Yakin ◽  
Maulidya Octaviani Bustamin
Keyword(s):  
Secondary Data ◽  
Working Hours ◽  
Project Work ◽  
Time Cost ◽  
Trade Off ◽  
Overtime Work ◽  
Critical Paths ◽  
The Cost ◽  
Total Project

In the implementation of construction project activities there are thre things that influence the success and failure of the project: time, cost and quality. The success of a project is usually seen from the timing of completion which is relatively short but without neglecting the quality of the project work. Appropriate and targeted project management and management are required to ensure the time, cost, and quality of the project. This is certainly to avoid a variety of undesirable things such as late settlement, swelling costs, quality failures, and so on that could have an impact on project failure and the emergence of the cost of fines. The purpose of this study is to calculate changes in cost and time of project implementation with alternatives to additional working hours (overtime) comparing the results between normal and cost changes after the addition of working hours (overtime). The data used in this research is secondary data obtained from contractor implementing. Arrow diagram The results program are critical paths and cost increases due to the addition of working hours (overtime) while the result of the time cost trade off method is the acceleration of duration and the increased cost due to the acceleration of duration in any accelerated activity. The results of this study indicate that the total project time and cost under normal conditions is 508 days at a cost of Rp 22.240.655.701  with the addition of 3 hours of overtime work in the duration of crashing 485 days and at a cost of Rp 23.252.220.373,34

scholarly journals Integer linear programming outperforms simulated annealing for solving conservation planning problems

2019 ◽  
Author(s):  
Richard Schuster ◽  
Jeffrey O. Hanson ◽  
Matt Strimas-Mackey ◽  
Joseph R. Bennett
Keyword(s):  
Linear Programming ◽  
Simulated Annealing ◽  
Integer Linear Programming ◽  
Conservation Planning ◽  
Practical Advantage ◽  
Processing Times ◽  
Conservation Plans ◽  
The Cost ◽  
Planning Problems

AbstractThe resources available for conserving biodiversity are limited, and so protected areas need to be established in places that will achieve objectives for minimal cost. Two of the main algorithms for solving systematic conservation planning problems are Simulated Annealing (SA) and Integer linear programming (ILP). Using a case study in British Columbia, Canada, we compare the cost-effectiveness and processing times of SA versus ILP using both commercial and open-source algorithms. Plans for expanding protected area systems based on ILP algorithms were 12 to 30% cheaper than plans using SA. The best ILP solver we examined was on average 1071 times faster than the SA algorithm tested. The performance advantages of ILP solvers were also observed when we aimed for spatially compact solutions by including a boundary penalty. One practical advantage of using ILP over SA is that the analysis does not require calibration, saving even more time. Given the performance of ILP solvers, they can be used to generate conservation plans in real-time during stakeholder meetings and can facilitate rapid sensitivity analysis, and contribute to a more transparent, inclusive, and defensible decision-making process.

scholarly journals Comparing different ranking functions for solving fuzzy linear programming problems with fuzzy cost coefficients

2021 ◽  
Vol 4 (2) ◽  
pp. 3-17
Author(s):  
Betsabé Pérez Garrido ◽  
Szabolcs Szilárd Sebrek ◽  
Viktoriia Semenova
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Fuzzy Numbers ◽  
Fuzzy Linear Programming ◽  
Ranking Functions ◽  
Statistical Software ◽  
Linear Programming Problems ◽  
Fuzzy Cost ◽  
The Cost ◽  
Cost Vector

In many applications of linear programming, the lack of exact information results in various problems. Nevertheless, these types of problems can be handled using fuzzy linear programming. This study aims to compare different ranking functions for solving fuzzy linear programming problems in which the coefficients of the objective function (the cost vector) are fuzzy numbers. A numerical example is introduced from the field of tourism and then solved using five ranking functions. Computations were carried out using the FuzzyLP package implemented in the statistical software R.

scholarly journals A New Approach to Find an Optimal Solution of a Fuzzy Linear Programming Problem by Fuzzy Dynamic Programming

2018 ◽  
Vol 7 (4.10) ◽  
pp. 360
Author(s):  
T. Nagalakshmi ◽  
G. Uthra
Keyword(s):  
Dynamic Programming ◽  
Linear Programming ◽  
Objective Function ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Optimal Solution ◽  
Fuzzy Linear Programming ◽  
New Approach ◽  
The Cost ◽  
Recursive Equations

This paper mainly focuses on a new approach to find an optimal solution of a fuzzy linear programming problem with the help of Fuzzy Dynamic Programming. Linear programming deals with the optimization of a function of variables called an objective function, subject to a set of linear inequalities called constraints. The objective function may be maximizing the profit or minimizing the cost or any other measure of effectiveness subject to constraints imposed by supply, demand, storage capacity, etc., Moreover, it is known that fuzziness prevails in all fields. Hence, a general linear programming problem with fuzzy parameters is considered where the variables are taken as Triangular Fuzzy Numbers. The solution is obtained by the method of FDP by framing fuzzy forward and fuzzy backward recursive equations. It is observed that the solutions obtained by both the equations are the same. This approach is illustrated with a numerical example. This feature of the proposed approach eliminates the imprecision and fuzziness in LPP models. The application of Fuzzy set theory in the field of dynamic Programming is called Fuzzy Dynamic Programming. 

Including decision-makers preferences in the cost-deprivation trade-off during disaster interventions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Florian Diehlmann ◽  
Patrick Siegfried Hiemsch ◽  
Marcus Wiens ◽  
Markus Lüttenberg ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Humanitarian Logistics ◽  
Decision Makers ◽  
Weighted Sum ◽  
Trade Off ◽  
Content Type ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
The Cost

Purpose In this contribution, the purpose of this study is to extend the established social cost concept of humanitarian logistics into a preference-based bi-objective approach. The novel concept offers an efficient, robust and transparent way to consider the decision-maker’s preference. In principle, the proposed method applies to any multi-objective decision and is especially suitable for decisions with conflicting objectives and asymmetric impact. Design/methodology/approach The authors bypass the shortcomings of the traditional approach by introducing a normalized weighted sum approach. Within this approach, logistics and deprivation costs are normalized with the help of Nadir and Utopia points. The weighting factor represents the preference of a decision-maker toward emphasizing the reduction of one cost component. The authors apply the approach to a case study for hypothetical water contamination in the city of Berlin, in which authorities select distribution center (DiC) locations to supply water to beneficiaries. Findings The results of the case study highlight that the decisions generated by the approach are more consistent with the decision-makers preferences while enabling higher efficiency gains. Furthermore, it is possible to identify robust solutions, i.e. DiCs opened in each scenario. These locations can be the focal point of interest during disaster preparedness. Moreover, the introduced approach increases the transparency of the decision by highlighting the cost-deprivation trade-off, together with the Pareto-front. Practical implications For practical users, such as disaster control and civil protection authorities, this approach provides a transparent focus on the trade-off of their decision objectives. The case study highlights that it proves to be a powerful concept for multi-objective decisions in the domain of humanitarian logistics and for collaborative decision-making. Originality/value To the best of the knowledge, the present study is the first to include preferences in the cost-deprivation trade-off. Moreover, it highlights the promising option to use a weighted-sum approach to understand the decisions affected by this trade-off better and thereby, increase the transparency and quality of decision-making in disasters.

WARRANTY AND OPTIMAL UPGRADE STRATEGY FOR USED SYSTEMS: AN ELECTRIC DRILL CASE STUDY

2012 ◽  
Vol 29 (04) ◽  
pp. 1250023 ◽  
Author(s):  
MAHMOOD SHAFIEE ◽  
STEFANKA CHUKOVA ◽  
MAXIM FINKELSTEIN
Keyword(s):  
Functional State ◽  
Additional Cost ◽  
Practical Application ◽  
Trade Off ◽  
Action Strategies ◽  
Electric Drill ◽  
Warranty Cost ◽  
The Cost

Offering warranty for a second-hand item stimulates the sales of the item, but at the same time, it accumulates additional warranty servicing cost. This additional cost can be reduced through actions that improve the reliability of the item, such as overhaul and upgrade. An upgrade action brings the second-hand item to an improved functional state and it effectively reduces the age of the item. In this paper, we propose a model aiming to determine the optimal upgrade action strategies that achieve a sensible trade-off between the cost of an upgrade action and the reduction of the expected warranty cost due to this action. A practical application case on electric drills is used to illustrate our findings.

An Integer Programming Approach to Optimize the Plantation in Order to Reduce Global Warming

2012 ◽  
Vol 548 ◽  
pp. 767-771 ◽  
Author(s):  
C. Vanlisuta ◽  
Suksan Prombanpong
Keyword(s):  
Mathematical Model ◽  
Linear Programming ◽  
Objective Function ◽  
Programming Model ◽  
Programming Approach ◽  
Profit Function ◽  
Carbon Credit ◽  
Integer Linear Programming Model ◽  
The Mathematical Model

The objective of this paper is to determine the number and species of trees to be planted in order to maximize a profit through an integer linear programming model. The mathematical model is developed in terms of the profit function. This objective function is therefore, a difference between carbon credit revenue and costs of plantation. The economical plants are only considered in the model. Consequently, fourteen different tree species are to be investigated. The objective function is subjected to several constraints i.e. planting area, carbon sequestration and so on. The planting envelope of each tree is assigned 4 by 4 meters. In this paper, the Eastern part of Thailand is considered the case study. It is found that three kinds of plants, Copper pod, Cananga, and Bullet wood are suitable for planting. A number of trees to be planted in 1600 square meter are twenty, thirty, and fifty plants respectively. The profit earned is of 12,112 $ per year in the next fifth year.

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