Time and cost optimization using fuzzy goal programming

Subali, Made Agus Putra; Sarno, Riyanarto; Effendi, Yutika Amelia

doi:10.1109/icoiact.2018.8350723

Cited by 9 publications

(6 citation statements)

References 8 publications

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“…The goal of this optimization is to find optimum trade-off from time and cost spent for a project or system. Optimization could be done by several method, like PERT and Goal Programming [25], and fuzzy goal programming to optimize time and cost [33]. Goal programming is one of the widely used methods, and Data Envelopment Analysis (DEA) is one of goal programming formulation that could be used to define system efficiency.…”

Section: Optimizationmentioning

confidence: 99%

Standard Operating Procedure Optimization of Resource Level for Hospital Waste Handling Using Hybrid DES-ABM Simulation, Genetic Algorithm, and Goal Programming

Marsha¹,

Sarno²,

Sungkono³

2022

Proceedings of the 3rd International Conference on Business and Management of Technology (ICONBMT 2021)

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The emergence of the Covid-19 pandemic has caused several changes in healthcare services carried out by hospitals. Covid-19 has caused increasing waste generated from medical activities and operational service activities, in which the Standard Operating Procedure (SOP) has been adjusted due to new regulations to prevent cross-contamination during this pandemic. The increasing number of wastes generated and changes in SOP could have impacted on spending more costs for processing medical waste caused by Covid-19 operational services and causes longer service time. The purpose of this study was to find the optimum value of resource level based on operational costs and service time from the medical waste handling developed with hybrid Discrete Event Simulation -Agent-Based Modelling (DES-ABM) to capture real-time events. To find optimum value, optimization techniques such as Genetic Algorithm and Goal Programming are also used. Optimization from this research results in 17 alternatives of resource level from a total of 100 generations and 20 initial design point. The best design point found could reduce the waiting time by 26.87 minutes, reduce completion time by 506.82 minutes, and reduce cost IDR117,144 from the initial resource level used by the hospital.

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Section: Optimizationmentioning

confidence: 99%

Standard Operating Procedure Optimization of Resource Level for Hospital Waste Handling Using Hybrid DES-ABM Simulation, Genetic Algorithm, and Goal Programming

Marsha¹,

Sarno²,

Sungkono³

2022

Proceedings of the 3rd International Conference on Business and Management of Technology (ICONBMT 2021)

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“…Generalization value ranges from 0 to 1, where 0 means the model shows specific form from the event logs, while 1 means it shows a more flexible form as a comparation from event logs discovery of nodes. Generalization value (GV) could be measured by (4).…”

Section: Sv = 1 -Duplicate Activities + Missing Activities Nodes On Model (2) -Precisionmentioning

confidence: 99%

“…Nowadays, process mining become more popular in organization or company because by using its methods organization could easily capture information from each transaction happened [2]. Some previous research used program evaluation and review technique (PERT) [3] and goal programming [4] to optimize time and cost, where PERT is used to select optimal trace of the project and Goal Programming defined the goal itself. In this research, fuzzy miner approach will be used to extract process model with less structured processes [5].…”

Section: Introductionmentioning

confidence: 99%

Improved fuzzy miner algorithm for business process discovery

2021

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Return material authorization (RMA) is a process in which a company decides to repair or replace customer's defect product during the warranty period. To execute RMA, both company and customer obliged to follow standard operating procedure (SOP) which usually consists of many business processes of a company well. As the business process could cause inefficiencies, a company should improve their business process regularly. The best way is using process discovery. This research proposes a new improved fuzzy miner algorithm to represent binary correlation between activities. This new algorithm utilizes binary significance and binary correlation equally to acquire fuzzy model. While the original fuzzy miner algorithm uses various binary correlation metrics, the improved fuzzy miner algorithm uses only one metric and could capture the fuzzy model, accurately based on the event logs to capture more accurate business process model. In this research, ProM fuzzy miner is used as a comparison to the proposed improved time-based fuzzy miner. The results showed that the improved algorithm has higher value on conformance checking and able to capture business process model based on time interval, by using only time-interval significance as a binary correlation metrics.

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“…The GP model was enhanced using fuzzy set theory [22] to manage uncertainty data, resulting in FGP. The main goal is to improve the ability of FGP to deal with the nature of uncertainty when modeling problems [26,27]. Uncertainties are frequently related to the goal objectives in a case such as a production planning model.…”

Section: Fuzzy Goal Programming (Fgp)mentioning

confidence: 99%

Hybrid Uncertainty-Goal Programming Model with Scaled Index for Production Planning Assessment

Watada

Arbaiy

Chen³

2021

FinTech

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Goal programming (GP) can be thought of as an extension or generalization of linear programming to handle multiple, normally conflicting objective measures. Each of these measures is given a goal or target value to be achieved. Unwanted deviations from this set of target values are then minimized in an achievement function. Production planning is an important process that aims to leverage the resources available in industry to achieve one or more business goals. However, the production planning that typically uses mathematical models has its own challenges where parameter models are sometimes difficult to find easily and accurately. Data collected with various data collection methods and human experts’ judgments are often prone to uncertainties that can affect the information presented by quantitative results. This study focuses on resolving data uncertainties as well as multi-objective optimization using fuzzy random methods and GP in production planning problems. GP was enhanced with fuzzy random features. Scalable approaches and maximum minimum operators were then used to solve multi-object optimization problems. Scaled indices were also introduced to resolve fuzzy symbols containing unspecified relationships. The application results indicate that the proposed approach can mitigate the characteristics of uncertainty in the analysis and achieve a satisfactory optimized solution.

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Time and cost optimization using fuzzy goal programming

Cited by 9 publications

References 8 publications

Standard Operating Procedure Optimization of Resource Level for Hospital Waste Handling Using Hybrid DES-ABM Simulation, Genetic Algorithm, and Goal Programming

Standard Operating Procedure Optimization of Resource Level for Hospital Waste Handling Using Hybrid DES-ABM Simulation, Genetic Algorithm, and Goal Programming

Improved fuzzy miner algorithm for business process discovery

Hybrid Uncertainty-Goal Programming Model with Scaled Index for Production Planning Assessment

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