Decision Support for Plan Adaptation in Unforeseen Situations

Handling irregular phenomena might bring great complexity for involved teams. Variables considered for undertaking recommended procedures may yield many decision alternatives, challenging to deal with at planning time. Additionally, expectations regarding the phenomena handling may not match those observed. This means that the existing plan’s application may become inappropriate, and teams must be creative in performing actions and decision-making. An approach for on-the-fly adaptation of plans aims to assist teams in identifying and diagnosing unforeseen situations, besides adjusting previously developed plans at runtime. This approach was evaluated through experiments in the emergency management domain, and the initial results indicate its feasibility in dealing with unforeseen situations while handling irregular phenomena in complex environments.

A Multi-Agent Linguistic-Style Large Group Decision-Making Method Considering Public Expectations

Focusing on the characteristics of public participation and large group decision making of major livelihood projects, this paper proposes a multi-agent linguistic-style large group decision-making method with the consideration of public expectations. Firstly, based on the discrimination degree of evaluating information, the comprehensive weight of each attribute is calculated with the principle of maximum entropy. Secondly, the expert preference information for different alternatives is clustered and several aggregations are formed. Thirdly, the preference conflict level of experts' group for each alternative is calculated, and a conflict-oriented experts' aggregation weight optimization model is constructed to ensure the effectiveness of conflict resolution. Fourthly, the public group's satisfaction is determined with the expectation distribution of public’s and the expert group's preference, so as to obtain the sorting result of the decision alternatives. Finally, the effectiveness and applicability of the proposed method are verified by method comparison.

Web-Based Recruitment Selection Application Development with Analytical Hierarchy Process (AHP) Method

This research aimed to design and develop a support system to determine the selection of recruitment, especially assistant for the Integrated ICT Laboratory at Budi Luhur University according to predetermined criteria. The method used in developing the application was the Analytical Hierarchy Process (AHP) method, which was to rank decision alternatives and accept the excellence one for several criterion cases that mixes qualitative and quantitative components in the whole assessment of available alternatives. The results showed that there were 6 (six) criteria in the selection of the Integrated ICT Laboratory Assistant, including Attendance Value, Competency Value, Project Value, Hardware Value, Interview Value, and Psychological Test Value, which were in accordance with the criteria in the Integrated ICT Laboratory at Budi Luhur University. The system can speed up the process of accepting assistants, because the calculation process, as well as printing the final score are in one system, according to the terms and criteria specified, making it more effective and efficient.

STRATEGI PEMASARAN ROTI DI KING’S BAKERY DENGAN METODE ANALYTICAL HIERARCHY PROCESS (AHP)

ABSTRACT Every industry must make gradual improvements in order to be able to compete in the era of globalization. King's Bakery is a home industry that produces bread. The condition of bread marketing in the King's Bakery business has not been maximized. This study aims to determine the order of priority criteria and sub-criteria in the selection of a bread marketing strategy at King's Bakery and which strategy should be chosen by King's Bakery based on the Analytical Hierarchy Process (AHP) method. Analytical Hierarchy Process (AHP) is a method for ranking decision alternatives and selecting the best one with several criteria. The Analytical Hierarchy Process (AHP) develops a numerical value to find a ranking or priority order of various alternatives in solving a problem, based on the extent to which each alternative meets the decision maker's criteria. The results of this study obtained an assessment of the importance of the criteria in the selection of a bread marketing strategy showing the following priority or weighting scale: the first priority was place (0.546), the second and third priorities are products and distribution channels with the same value (0.231), and the fourth priority was the organization (0.104). From the results of the assessment of the level of alternative importance in the selection of bread marketing strategies, the priority scale or weights are as follows: the first priority was strategy A (3.614), the second priority was strategy C (2.366), the third priority was strategy B (2,000). The best bread marketing strategy that can be used as an alternative to improve bread marketing was strategy A, because it has the highest overall weight value. With technological innovation, it will accelerate production and facilitate marketing for the company.

Evaluation of tanker vehicle selection using a novel hybrid fuzzy MCDM technique

Petroleum product transportation considered as one of the crucial parts of dangerous material transportation is a risky logistics activity. The selection of the appropriate tanker vehicles may be a suitable solution to reduce the risks and increase the efficiency and performance of the fuel transportation companies. However, the selection of a suitable road tanker vehicle is not an easy task for decision-makers as there are many conflicting criteria and many decision alternatives. In addition, decision-makers may have to decide with insufficient information since collecting crisp values may not be possible at all times. Hence, many ambiguities affecting the evaluation results exist in an assessment process performed to select the best tanker vehicle option. This paper suggests a novel integrated fuzzy approach to solve these decision-making problems. Sensitivity analysis is conducted to test the validation of the proposed integrated fuzzy approach and its results was performed by forming 130 scenarios. The results of sensitivity analysis prove that the proposed model can be applied to solve these kinds of decision-making problems.

Designing Decision Support System for Midwifery Students’ Tuition Fees Problem

Education is an essential need and an important element to create a broad-minded youth. While in Indonesia, the rate of tuition fees is still imbalanced with the economic rate. Thus, many people decided to discontinue their higher education. Decision making plays an important role to manage organizations, including in educational institutions, as one of the main duties in managerial is making decisions. This study took place in a midwifery academy in Malang. In response to this situation, the academy has a policy to alleviate students by paying the tuition fees in instalments. However, many students are in arrears as the result of this policy. Thus, management needs to take some consideration before making a decision toward the problem. Those considerations require high accuracy and time consuming to process information that support decision making. Currently, the decision-making process in this academy is still semi-automated, in which some processes are still done manually, which affect longer time to make decisions, and the accuracy of calculations could not be fully guaranteed. According to this condition, the purpose of this research is to design a decision support system that enables us to process information for decision making and to offer decision alternatives for decision makers. This research employs Systems Development Life Cycle (SDLC) with a decision table as a method to create decision alternatives. The prototype was developed using Visual Studio C#.Net. The result shows that by using the proposed prototype of DSS, decision makers can reduce 5-10 minutes of decision making process compared to the old semi-automated system which still required manual calculation and data collection and analysis before making the decision. A complete data and more detailed parameters for decision criteria are required to implement the proposed prototype of DSS in the institution with more objective consideration in the decision making process as the future work.

Knowledge visualisation for construction procurement decision-making: a process innovation

PurposeIn the construction sector, the knowledge-based process outgrows its emphasis on technological aspects. Yet, there is a lack of applied studies showing how a procurement system (PS) could be selected in the digital age. In particular, there is a radical need to establish an innovative process to visualise novel PS decision. Therefore, this paper aims to present a knowledge visualised framework for aiding construction PS decision-making.Design/methodology/approachThis paper describes the construction of process innovation. The framework (process) is supported by four influential decision supporting methods (mean utility values, analytic hierarchy process, fuzzy set theory and Delphi method) and computer programming (Matlab).FindingsThere are four stages of this framework: (1) uniform rating for decision alternatives; (2) group decision for determining the decision attribute; (3) determining the final choice; (4) reporting the cognitive computing process. Supported by individual and groups decision dynamics, this framework emphasises how the dashboard aided innovative approach enables the induction of understanding, cognitive computing for decision-making and how the information would precisely be represented, which are vital requirements of modern construction.Originality/valueThe contribution of this paper presents two leverage points that support the modern PS decision. Firstly, this paper provides a holistic view of the decision supporting methods on the basis of how a suitable PS would be systematically sought. Based on the existing studies, this paper upgrades into a visualised knowledge decision supporting process. It helps the participants understand and improve their cognitive learning. Secondly, this framework allows the participants to have a view of the individual and group decisions. It sheds light on the development of the collaborative decision-making process.

Meta-Decision in Healthcare

Meta-decision as a junction between evidence and its rightful implementation is suggested in this review as a structured framework applied in healthcare, valuable to clinicians and healthcare decision-makers. The process of meta-decision requires optimum measurements to provide data necessary for identifying and developing decision alternatives and explicitly reflect on its value and choose the optimum decision. The location of value in the meta-decision framework is core component. Of equal importance are prerequisites for decision-makers' abilities to make meta-decisions and focus on optimum team environments. As well as improving their decision-making process through reflection and learning.

Personalized Multi-Criteria Decision Strategies in Location-based Decision Support

Location-based services (LBS) assist people in decision-making during the performance of tasks in space and time. Current LBS support spatial and attribute queries, such as finding the nearest Italian restaurant from the current location of the user, but they are limited in their capacity to evaluate decision alternatives and to consider individual decision-makers’ user preferences. We suggest that LBS should provide personalized spatial decision support to their users. In a prototype implementation, we demonstrate how user preferences can be translated into parameters of a multi-criteria evaluation method. In particular, the Ordered Weighted Averaging (OWA) operator allows users to specify a personal decision strategy. A traveler scenario investigating the influence of different types of users and different decision strategies on the outcome of the analysis serves as a case study.

Personalized Multi-Criteria Decision Strategies in Location-based Decision Support

Location-based services (LBS) assist people in decision-making during the performance of tasks in space and time. Current LBS support spatial and attribute queries, such as finding the nearest Italian restaurant from the current location of the user, but they are limited in their capacity to evaluate decision alternatives and to consider individual decision-makers’ user preferences. We suggest that LBS should provide personalized spatial decision support to their users. In a prototype implementation, we demonstrate how user preferences can be translated into parameters of a multi-criteria evaluation method. In particular, the Ordered Weighted Averaging (OWA) operator allows users to specify a personal decision strategy. A traveler scenario investigating the influence of different types of users and different decision strategies on the outcome of the analysis serves as a case study.