Cost Criterion Research Articles

Modeling and solving the multi-objective energy-efficient production planning and scheduling with imperfect maintenance activities

PurposeThe purpose of this study is to propose a new mathematical model that integrates strategic decision-making with tactical-operational decision-making in order to optimize production and scheduling decisions.Design/methodology/approachThis study presents a multi-objective optimization framework to make production planning, scheduling and maintenance decisions. An epsilon-constraint method is used to solve small instances of the model, while new hybrid optimization algorithms, including multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm, multi-objective harmony search and improved multi-objective harmony search (IMOHS) are developed to address the high complexity of large-scale problems.FindingsThe computational results demonstrate that the metaheuristic algorithms are effective in obtaining economic solutions within a reasonable computational time. In particular, the results show that the IMOHS algorithm is able to provide optimal Pareto solutions for the proposed model compared to the other three algorithms.Originality/valueThis study presents a new mathematical model that simultaneously determines green production planning and scheduling decisions by minimizing the sum of the total cost, makespan, lateness and energy consumption criteria. Integrating production and scheduling of a shop floor is critical for achieving optimal operational performance in production planning. To the best of the authors' knowledge, the integration of production planning and maintenance has not been adequately addressed.

Optimization of carbon dioxide ejector expansion transcritical refrigeration system with ANOVA and NSGA-II

With a projected increase of over 30 % by 2050, refrigeration systems are already responsible for 17 % of all electrical energy. To address these critical environmental concerns and enhance overall efficiency while reducing costs, a shift to eco-friendly and neutral impact alternatives is imperative. When carbon dioxide (CO2) is used as a working fluid since it is a natural gas, coupled with optimized system configurations, it holds the promise to mitigate these challenges effectively. In this study, a novel transcritical refrigeration cycle with an ejector operating with CO2, is proposed to further improve system efficiency. To validate the system's performance, a comprehensive thermodynamic model was established, and published results were used for validation. Remarkably, the new system demonstrated higher energy and exergy efficiency when compared to existing systems documented in the literature. To identify the most influential factors affecting cycle performance, an ANOVA analysis was conducted. The evaporator temperature was shown to be the most important variable, impacting the COP, exergy efficiency, and overall cost of the product by a combined 81, 46, and 75 %, respectively. In addition, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) method was used to maximize the effectiveness of the system. This method of multi-objective optimization took into account both the thermodynamic criterion of exergy efficiency and the economic criterion of total product cost. The integration of these criteria in the optimization process allows for an environmentally friendly and economically viable NEETR cycle.

Ship route simulation based on the cluster analysis

The problem of safe ship’s route planning at the variable hydrometeorological situation along the route is considered in the paper. The problem solved in the paper is based on the division of the water area into separate clusters, depending on its characteristics. The route from Busan Port to Kushiro Port is used as an example. The specifics of this route is that it runs through the open sea, and through the straits and archipelagos. The aim of the work is to automate the process of planning the route and adjusting it during the trip, depending on changes in external conditions. The graph theory for modeling a route is proposed in this paper. The construction of graphs is implemented using the cluster analysis method. In the analysis, the water area of the route is divided into separate subareas, depending on the distance to the coast and the depths difference. Open water areas are separated into larger clusters. Near the coast and at shallow depths, clustering is shorter. The cluster centroids are the vertices of the graphs of the future route. As result it is a simulation of graphs of different sizes. The union of graphs forms the hypergraph. The distance is used as the weight of the graph edges. To determine the most preferable route in criteria of speed, cost or safety, weights are added depending on weather and other factors. As a result of this approach, several routes are planning on the hypergraph. Depending on the weight of the priority criteria, a route is selected automatically. The proposed method can be used to create systems for automated planning of optimal routes, taking into account the selected criteria under changing environmental conditions in the process of voyage and replanning it if necessary.

Contribution of cabotegravir + rilpivirine long-acting for the treatment of HIV-1 infection

ObjectiveTo determine the value contribution of cabotegravir + rilpivirine, the first injectable every two months long-acting antiretroviral regimen, using multi-criteria decision analysis. MethodThe study was developed in two phases. After a small pilot, a field work study with a larger number of multidisciplinary experts was carried out. Seven single-tablet regimens, currently recommended by the GeSIDA guidelines, were selected as comparators. EVIDEM methodology was followed, with a framework composed by 12 quantitative and 5 contextual criteria. Mean and standard deviations were calculated for quantitative criteria (1 to 5 scale; comparative criteria -5 to +5), whereas qualitative criteria were analyzed as percentages of experts that considered a positive, neutral or negative impact for the National Health System. Results: 35 experts participated in the study. Human immunodeficiency virus-1 infection was considered severe (mean ± standard deviation: 3.0 ± 1.0), with moderate size of affected population (2.7 ± 1.2) and unmet needs (2.8 ± 1.0). Minimal differences were found in comparative efficacy/effectiveness (0.1 ± 0.5), safety/tolerability (-0.5 ± 0.7), and cost criteria: cost of the intervention (0.5 ± 2.0), other medical costs (0.2 ± 1.8) and non-medical/indirect costs (0.5 ± 1.6). Experts perceived an improvement with cabotegravir + rilpivirine long-acting, compared to current daily oral single-tablet regimens, in patient-reported outcomes (2.7 ± 1.4). Therapeutic benefit of the long-acting regimen was considered moderate-to-high (3.5 ± 1.2). Experts considered the evidence provided by cabotegravir + rilpivirine long-actingrobust (4.3 ± 0.8), with elevated consensus on its future recommendation in guidelines (3.2 ± 1.0). In contextual criteria, most experts considered positive the impact on population priorities and access (91%), common goal and specific interests (63%) and political, historical, and cultural context criteria (60%). Impact was neutral in system capacity and appropriate use (40%), and opportunity costs and affordability criteria (51%). Result of the weighted global value contribution of cabotegravir + rilpivirine long-acting was 0.34 (-1 to +1 scale), with Patient Reported Outcomes comparative criterion bringing the highest added value. ConclusionsCabotegravir + rilpivirine long-acting provides added value contribution to human immunodeficiency virus-1 management in Spain compared to daily oral single-tablet regimens. Patient Reported Outcomes and therapeutic benefit of cabotegravir + rilpivirine long-acting were highly valued by experts, as the expected benefit in adherence and stigma-related issues would improve overall quality of life for people living with human immunodeficiency virus-1.

On Strategic Measures and Optimality Properties in Discrete-Time Stochastic Control with Universally Measurable Policies

This paper concerns discrete-time infinite-horizon stochastic control systems with Borel state and action spaces and universally measurable policies. We study optimization problems on strategic measures induced by the policies in these systems. The results are then applied to risk-neutral and risk-sensitive Markov decision processes to establish the measurability of the optimal value functions and the existence of universally measurable, randomized or nonrandomized, ϵ-optimal policies, for a variety of average cost criteria and risk criteria. We also extend our analysis to a class of minimax control problems and establish similar optimality results under the axiom of analytic determinacy. Funding: This work was supported by grants from DeepMind, the Alberta Machine Intelligence Institute (AMII), and Alberta Innovates-Technology Futures (AITF).

Age of Information Cost Minimization with No Buffers, Random Arrivals and Unreliable Channels: A PCL-Indexability Analysis

Over the last decade, the Age of Information has emerged as a key concept and metric for applications where the freshness of sensor-provided data is critical. Limited transmission capacity has motivated research on the design of tractable policies for scheduling information updates to minimize Age of Information cost based on Markov decision models, in particular on the restless multi-armed bandit problem (RMABP). This allows the use of Whittle’s popular index policy, which is often nearly optimal, provided indexability (index existence) is proven, which has been recently accomplished in some models. We aim to extend the application scope of Whittle’s index policy in a broader AoI scheduling model. We address a model with no buffers incorporating random packet arrivals, unreliable channels, and nondecreasing AoI costs. We use sufficient indexability conditions based on partial conservation laws previously introduced by the author to establish the model’s indexability and evaluate its Whittle index in closed form under discounted and average cost criteria. We further use the index formulae to draw insights on how scheduling priority depends on model parameters.

Optimal Selection of Conductors in Distribution System Designs Using Multi-Criteria Decision

The growth in the demand for electrical energy, which is driven by the constant growth of the metropolises and the expansion of the productive capacities of the industrial sector, entails the inevitable development of the electrical system to satisfy all the required demands in a convenient, efficient, and reliable manner. In this scenario, power distribution companies will continue to need to expand their electrical systems in the short and medium term to obtain the lowest investment and operating prices for the period considered in the analysis horizon. The expansion of the system can be projected statically or dynamically, which depends on the criteria that each distributor, in turn, applies in their expansion projects. Multi-criteria decision making can provide deeper analysis perspectives considering infinite possibilities for optimal network sizing and the technical, operational, quality of service, and even system reliability factors. This research proposes a multi-criteria decision technique based on the CRITIC method to determine the optimal design of an electrical distribution system. For this purpose, several design scenarios are defined with different types of electrical conductors, and the power flows are calculated in each. From these simulations, the results obtained in voltage profiles, namely active and reactive power losses, current levels, and the costs associated with the conductors used, are recorded. With the multi-criteria technique, the winning alternative is the design scenario containing the best joint solutions for the analysis variables. The proposed methodology is validated in an IEEE 34-bar test system. The Matpower tool, available through Matlab, generates power flows for each proposed design case. The results obtained in the analysis variables are generated and stored in a decision matrix of 210 alternatives. The proposed method represents a novel and powerful alternative for design proposals of distribution systems considering quality, efficiency, and cost criteria.

A multi-criteria framework for the ecodesign of bio-based materials at early development stages

Ex-ante life cycle assessment (LCA) allows for a holistic environmental evaluation of novel products at research and development (R&D) stages when the potential for environmental improvement is higher. Multi-criteria decision analysis (MCDA) incorporates techno-economic attributes and considers decision-makers’ (DMs) perspectives. Thus, integrating ex-ante LCA and MCDA is key for R&D ecodesign. This article proposes a framework combining ex-ante LCA with multi-attribute value theory and stochastic multi-acceptability analysis (SMAA) for novel bio-based materials in four steps: i) Problem structuring, ii) LCA scope, inventory, and scale-up, iii) Performance table, elicitation, and MCDA calculations, and iv) Interpretation and recommendations. The LCA-MCDA framework provides a structured way to model upscaled environmental impacts and encompass technical and economic performances in a global value while considering novel materials' potential application and functionality. The framework is applied to lab-scale starch films for food packaging, comparing them with commercial polymers for cost, environmental, and technical criteria according to three DMs' perspectives (biopolymer/sustainability researchers). Materials, formulations, and scenarios are assessed on a 1-kg basis with properties as technical criteria. The commercial films outperform the novel films, primarily due to technical performance. Scale-up and plasticizer scenarios show potential for reducing environmental impacts but do not alter the ranking of alternatives. SMAA shows that the ranking highly depends on the criterion weights; conversely, individual DM's perspectives lead to similar results. Materials are also compared for equivalent properties (stiffness, strength, and moisture barrier) by applying material substitution factors. The most favorable results for the starch films are achieved for equivalent stiffness, thus suggesting further investigation for rigid applications. Furthermore, suggestions for applying the framework to other cases are provided. The LCA-MCDA framework facilitates the communication of LCA results with cost and technical performance, supporting R&D in dealing with trade-offs and identifying pathways toward more sustainable and competitive production of bio-based materials.

ANALISIS PENILAIAN KINERJA SUPPLIER PADA PT IDCSS

The best performance assessment of suppliers in the company is an effort to improve the quality of service and provide the best products to customers. The effort aims to keep the company competitive by minimizing discrepancies in the supply chain flow. Research was conducted on PT IDCSS to find the best performing suppliers in meeting the needs of artificial ornamental plant products, to minimize problems arising from the supply of inappropriate products. The method used in this research is the VPI frame worked Analytical Hierarchy Process (AHP) method with the main criteria of Quality, Cost, Delivery, Flexibility and Response which are divided into 17 sub-criteria. The results showed that the highest weights were the delivery criteria (0.389), cost (0.294), quality (0.157), response (0.108) and flexibility (0.052). The assessment results on supplier performance supplier MIS (0.260), YOH (0.256), FYG (0.244), CIL (0.129) and supplier SAM (0.112). This shows that supplier MIS has the best performance as a supplier of artificial ornamental plant products for PT IDCSS.

Formulating a design model for product platform architecture adopting integrated design approach considering variety, cost, and accessibility criteria

Formulating a design model for product platform architecture adopting integrated design approach considering variety, cost, and accessibility criteria

A multilevel decision-making approach for road infrastructure management

ABSTRACT The design of effective road safety countermeasures requires a network diagnosis supported by data. Moreover, infrastructures need to be ready for the introduction of vehicle-to-infrastructure communications to support technologies, as truck platooning. Ascendi, a motorway concessionaire, developed an action plan to decrease crash frequency and casualties that rests in data recorded by automatic vehicle counting devices. To have a good network representation, new equipment will provide more data, thus enhancing the selection of countermeasures. We developed a multilevel decision-support approach to define equipment location. The process stages correspond to three levels of analysis: (1) clustering for road segment classification (network level); (2) quantification of the devices to install ensuring similar coverage (concession level); (3) device allocation according to geographical and cost criteria (segment level). An iterative and participatory process involving Ascendi resulted in a proposal for adding 43 devices to the existing 72, increasing the network coverage to 39%.

METHODICAL APPROACHES TO ENHANCING BUSINESS PROCESSES THROUGH INNOVATION IMPLEMENTATION AT THE ENTERPRISE

Abstract. This article describes the importance of developing high technology and a competitive economy in Kazakhstan, as well as the significance of improving business processes and mechanisms to achieve this goal. The success of enterprises depends on the right strategy, competent leadership, the availability of resources and markets, and efficient business processes.
 The authors discuss the role of innovation in increasing turnover and production growth of enterprises in the modern world. They emphasize the need to quickly adapt production programs to changing customer demands and short product life cycles.
 Special attention is given to the complexity of assessing the beneficial effect of innovations, and two evaluation criteria are presented: the minimum cost criterion and the integrated quality indicator of innovations. It also mentions the use of expert or statistical methods when it is impossible to establish a quantitative relationship between quality indicators and costs.
 In addition, the article describes the establishment of a relationship between costs and comprehensive indicators of technical level and economic efficiency using correlation and regression modeling. A methodology is proposed, including traditional normative approaches and the "cost-effectiveness" method.
 Keywords: foreign economic relations, competitiveness, national economy, innovations, efficiency, quality, technology.

Event-triggered risk-sensitive smoothing for linear Gaussian systems

An event-triggered risk-sensitive smoothing problem for linear Gaussian systems is investigated in this paper. Due to the special cost criterion of the risk-sensitive estimation, the smoothed information state is first constructed under a newly defined reference measure. Its Gaussian density and recursive forms are derived by processing it into the combination of the forward and backward information states, both of which are proven to have Gaussian densities and evolve in linear recursions. A stochastic even-triggering condition is adopted to preserve the Gaussian property during the derivation. Then the proposed problem is reformulated equivalently under the reference measure, expressed by minimizing an integral involving the smoothed information state, and finally solved by utilizing the Gaussian densities of information states. The applicability and effectiveness of the results are illustrated through a numerical example by comparisons with a naive risk-sensitive smoother and the event-triggered MMSE smoother.

Root Assessment Method (RAM): A novel multi-criteria decision making method and its applications in sustainability challenges

The major objective of this paper is to introduce a novel multi-criteria decision making method (MCDM) called Root Assessment Method (RAM) which is easy to understand, straightforward to use and comparable with other well-known MCDM methods. RAM is motivated by the shortcomings of existing MCDM methods to obtain a reliable result in a decision problem and also the fact that decision maker (DM) should understand the whole decision making process to be able to avoid possible computational pitfalls. To do so, we define an aggregating function to rank the alternatives based on a radical expression which its radicand and index are the sums of benefit and cost criteria of each alternative, respectively. Accordingly, RAM allows a different compensation degree between beneficial and non-beneficial criteria which is rare in existing MCDM methods. As the advantages of RAM, the ranking result is not influenced by additional parameter, beneficial and non-beneficial criteria can be simultaneously considered without any transformation and pairwise comparisons are not used. On the other hand, it is observed that RAM can provide the advantage of preventing rank reversal in two case studies, whereas TOPSIS and VIKOR are subject to this problem in the same cases. As another contribution, a new heuristic procedure is suggested to compare the ranking results obtained by RAM with other methods. Ten numerical examples demonstrate that RAM results are consistent with its presumed function and are easily interpretable for a DM who may not be well acquainted with theoretical aspects of MCDM methods. Examples are positioned in the field of sustainability research as the area with wide application of MCDM methods. The results provided by RAM are encouraging and we hope this method contributes to enrich decision theory.

Geospatial modeling for planning an optimum and least-cost route to link three historical sites in El-Fayoum desert, Egypt

Improving the accessibility to archaeological sites in a desert is a crucial issue; it enhances the landscape value and helps in achieving sustainable tourism development. El-Fayoum Oasis and Governorate in Egypt, has a unique heterogenic environment that encompasses desert, lakes, agriculture lands, and urban areas. It is quite rich in historical heritage reflected by abundant archaeological and cultural sites, many of which fall in desert zones. A main constraint is the poor or lack of accessibility to such sites. In this study, we designed a geospatial model for planning a sustainable least cost tourist route (path) to link and develop three archaeological sites namely; Madinet Madi, Watfa city and Ummal-Barijat ruins. Spatial multicriteria decision analysis was integrated with the analytical hierarchy process (AHP) and the least cost path modules. Three cost criteria themes were created associated with economic, social and environmental costs. A cost surface and a least-cost path were created for each criterion and for each theme. The themes were combined using weighted linear combination to create four least cost scenarios for the path. Five preference criteria were used to compare the four route scenarios. Results show that the environmental scenario scored first scoring 0.69 while the economy path scores second 0.42, the equal weights path scores third 0.40 and finally the social path comes to be the last having a preference score 0.36. The method is flexible because priority can be changed and adapted according to specifications and site variances. It can be helpful for decision makers and planners in planning routes based on visual maps and priority visions.

MATHEMATICAL MODEL OF THE AUTOMATION OF THE COMMON RAIL SYSTEM DIAGNOSTIC PROCESS OF THE YAMZ-5340 SERIES DIVIGUNS

Failures of systems and mechanisms of the internal combustion engine are among the first among the total number of failures of tractors and cars. To determine them, a significant number of methods and means of determining the technical condition (diagnosis) are used. Functional-cost analysis is a heuristic method aimed at identifying the possibilities of reducing the cost and increasing the quality of the object, which is considered as a system with an orientation to a functional approach at all stages of its life cycle. This scientific article presents a functional and cost analysis of the anti-lock braking system of cars. A functional model of this system was developed and its functions were classified. The classification of the functions of the functional model of the anti-lock braking system of cars is also presented. The utility coefficients of this system are actually determined by constructing a matrix of advantages according to the known methodology. The generalizing cost criterion in the design of technical and production systems takes into account costs at all stages of the system's life cycle. To estimate these costs, a matrix of the anti-lock braking system of cars was created, with which the cost factors are calculated. Constructed function utility diagrams, function location, function-cost and cost diagrams allowed to use the functions of the anti-lock braking system of cars, which have a positive function-cost indicator and the highest rating among the presented functions. Such an operation or functions, marked by the highest functional value indicator and rank, are key to the further development of the system or the achievement of the goal of the analysis.

FUNCTIONAL-COST ANALYSIS OF THE ANTI-LOCK BRAKING SYSTEM (ABS) OF CARS

Functional-cost analysis is a method that has a heuristic nature and is used to identify opportunities to reduce costs and improve the quality of an object, which is considered as a system with a functional orientation at all stages of its life cycle. This article considers the application of functional cost analysis for the anti-lock braking system of cars. As part of this study, a functional model of the car's anti-lock braking system was developed and its functions were classified. The classification of functions within the framework of the functional model of the anti-lock braking system of cars was also carried out. To determine the utility coefficients of this system, a matrix of priorities was built using a known calculation method. When designing technical or production systems, the general cost criterion takes into account costs at all stages of the system's life cycle. For this evaluation, a matrix of anti-lock braking system of cars was created, which allows to compensate the cost factor. The results of the study are the construction of a diagram of the utility of the functions of the anti-lock braking system of cars, a diagram of the location of the system functions taking into account the utility factor, a functional cost diagram of the system, a diagram of the costs of the system functions, a diagram of the location of the system functions taking into account the cost factor, a diagram of the value of the indicator of the functional cost of the system functions, and diagrams of the location of system functions with the calculation of the functional cost indicator. Based on the analysis of this diagram, the functions of the anti-lock braking system of the car were determined, which have a positive functional value indicator and the highest rating among the functional functions. operations or functions that have the highest functional value indicator and rank.

Was wird unter einer Public-Health-Intervention verstanden? Ergebnisse eines Delphi-Prozesses im deutschsprachigen Raum

BackgroundInternationally, a variety of definitions for public health interventions (PHI) exist. In the German-speaking countries, however, a definition is still outstanding. Therefore, the aim of this study was to derive consensus criteria for the definition of PHI from the expert perspective of science and practice. MethodsA Delphi survey with two online rounds was conducted from December 2022 to February 2023. Six criteria were formulated by a working group and posed for consensus: 1) the intention of the intervention, 2) potential conflicts of interest of the initiators of the intervention, 3) primary vs. secondary/tertiary prevention, 4) costs, 5) targeting, and 6) the reach of the intervention. In both Delphi rounds, experts from academia and practice were recruited through relevant networks and associations throughout the German-speaking world. The judgments were asked about standardized rating scales with the possibility of open justification. ResultsIn the first Delphi round, n = 52 and in the second round n = 43 experts from research, care and administration/management in health care participated. Consensus was reached on four of the six criteria after the second Delphi round: the intention of the intervention, possible conflicts of interest of the initiators of the intervention, primary vs. secondary/tertiary prevention, and the scope of the intervention. From the perspective of the experts interviewed, these are the criteria that distinguish PHI. Discussion and conclusionBased on the consensus criteria, PHI can be defined more concretely. Thus, the results contribute to a better inter- and transdisciplinary understanding. Ideally, the criteria will make it easier to assign interventions to the public health sector in the future, even if a precise examination will be necessary in individual cases, among other things because the experts disagreed on the criteria of costs and how to address the target group.

A NOVEL MODEL PROPOSAL FOR GREEN SUPPLIER SELECTION: AN APPLICATION IN THE RETAIL INDUSTRY

Today, good relations between companies and suppliers provide companies with a competitive advantage. Determining the supplier selection criteria and rewarding the suppliers by evaluating them at certain times is of great importance in establishing successful relations with the suppliers. For these reasons, in this study, it is aimed to determine and weight the criteria to be considered in the supply of products and fabrics in companies operating in the textile sector and to present the best results to green suppliers. In line with the determined purpose, studies were carried out in a retail company located in Istanbul from the textile sector. Supplier evaluation criteria were collected from the company and other studies in the literature and analyzed in two areas as main and sub-criteria. The evaluation of 34 different sub-criteria under the main criteria of cost, quality, delivery, flexibility, environmental management, technology and social was made by 3 experts. In the solutions of the evaluations, the best-worst method was preferred. The criteria weights determined according to the Best-Worst method were evaluated with the Weighted Aggregated Sum Product Assessment method and the ranking of 9 suppliers was revealed. Excel program was used during the analysis of the data.

Component-Based Test Case Generation and Prioritization Using an Improved Genetic Algorithm

Developing test cases is the most challenging and crucial step in the software testing process. The initial test data must be optimized using a strong optimization technique due to many testing scenarios and poor testing effectiveness. Test prioritization is essential for testing the developed software products in a production line with a restricted budget in terms of time and money. A good understanding of the trade-off between costs (e.g. time and resources needed) and efficiency (e.g. component coverage) is necessary to prioritize test case scenarios for one or more software products. So, this paper proposes an efficient Multi-objective Test Case Generation and Prioritization using an Improved Genetic Algorithm (MTCGP-IGA) in Component-based Software Development (CSD). A random search-based method for creating and prioritizing multi-objective tests has been employed utilizing numerous cost and efficacy criteria. Specifically, the multi-objective optimization comprises maximizing the Prioritized Range of test cases (PR), Pairwise Coverage of Characteristics (PCC), Fault-Finding Capability (FFC), and minimizing Total Implementation Cost (TIC). For this test prioritizing problem, a unique fitness function is constructed with cost-effectiveness metrics. IGA is a robust search technique that exhibits excellent benefits and significant efficacy in resolving challenging issues, including ample space, multiple-peak, stochastic, and universal optimization. Relying on the use of IGA, this paper classifies, computes the objective function, introduces the Nondominated Sorting Genetic Algorithm-II (NSGA-II) method, evaluates each branch’s proximity on the handling route, and arranges the path set to get the best answer. The outcomes demonstrate that the proposed MTCGP-IGA with NSGA-II performed the best than other baseline algorithms in terms of prioritizing the test cases (mean value of 195.2), PCC (mean score of 0.7828), and FFC (mean score of 0.8136).