Designing an efficient supply chain for organ transplant networks which is intimately related to humans’ life plays a primary role in improving the network’s performance. This research is focused on proposing a new multi-period location-allocation modeling approach to make appropriate strategic decisions for designing organ transplant networks under supply and budget uncertainties. To serve this purpose, a bi-objective possibilistic programming model is formulated the aim of which is to maximize network responsiveness and minimize the total cost. A fuzzy goal programming approach is adopted to solve multiple objective function models and control their deviations from the corresponding aspiration levels. As an important contribution of this study, the chance of success of transplantation processes is taken into consideration by proposing appropriate utility functions according to transportation criteria. Moreover, for the purpose of coping with the inherent uncertainty of the input parameters, a possibilistic programming model based on Me measure converted to three optimistic, realistic and pessimistic models is developed. Three new formulations have also been developed to tackle equality chance constraints. Finally, the optimal solutions of the developed models are analyzed through conducting a real case study in Iran. According to the results, for the considered organ transplant network, the possibilistic programming model based on the realistic measure is better than the optimistic and pessimistic measure in most confidence levels.

Home health care faces new challenges day by day and it has become increasingly legitimate in the face of an aging population. Home healthcare centers are exposed to cumulative demands and academics are paying attention to the routing and scheduling matter, which is offered in literature as a Technician Routing and Scheduling Problem (TRSP) where the aim is to minimize the total cost subject to the time windows constraints to serve the patients respecting their priorities. In this paper, we develop a new distributed algorithm to resolve the home health care routing and scheduling problem (HHRSP). The principal idea of this algorithm is to apply artificial intelligence techniques in a distributed optimization method. The integration of automatic learning and search methods are applied to optimize the assignment of appointments to home caregivers. It allows us to gain time, effort, especially cost, and while complying with the problem constraints. The comparison results prove the efficacy of the recommended approach, which can offer decision support for medical executives of home health care.

This research deals with a multi-job Integer batch scheduling problem on a single machine with different due dates. Every job demanded one or more parts, and the single machine processed the job into a number of batches. The objective is to minimize total actual flow time, defined as the total flow time of all jobs starting from the arrival to the common due date. The decisions are to determine the sequence of jobs, the number of batches, batch size, and sequence of all batches on a single machine. This research proposes three algorithms, developed based on the longest due date rule (The P1-LDD Algorithm), the adjacent pairwise interchange method (The P2-API Algorithm), and the permutation method (The P3-PM Algorithm). The numerical experience shows that the three algorithms produce an outstanding solution. The P1-LDD Algorithm fits to solve a simple problem. The P2-API Algorithm has superior to solve a big complicated problem. The P3-PM Algorithm has the best performance to solve small complicated problems.

The palm oil industry has a strategic role in economic development in Indonesia, especially in alleviating poverty and creating other businesses that can support the industry. Operational activities in the palm oil industry are closely related to environmental issues (deforestation, land-use change, and air pollution) and social conflict. The certification program is an effort for the palm oil industry to implement sustainable development. The certified palm oil industry will increase industrial profitability in the long run to increase investor interest in the future. The decision to choose palm oil industry stocks that carry out sustainable practices and generate maximum returns is an exciting issue, but how investors can choose the right stocks and the minimum risk level. This study aims to apply the decision-making model to choose the optimal stock in the palm oil industry, which involves sustainable certification and risk criteria. The method used in this study was the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) based on the Indonesia Stock Exchange (IDX) data. Determinants of stock selection decisions from previous research are considered criteria for decision making. Through the PROMETHEE method, a list of the rankings of the oil palm industry shares can be generated. The sustainable certification and risk criteria can be used as a reference for relevant stakeholders such as investors. Further studies need to be developed by adding non-financial criteria in the firm and developing the criteria to differentiate each other.

The premium is a deterministic function to compensate for losses due to random events and it is an essential part of an insurance company operation. Numerous issues are faced by the Takaful operator in the practice of insurance, one of them is “validity of life insurance” which is still under discussion among Islamic scholars. Their conversation leads to the issue of approach which are utilised by the Takaful operator to create a sales illustration product. Based on their current discussion, there are still some hidden elements and some missing points related to the concept of loss and surplus sharing utilised by Takaful operator. Therefore, this paper focuses on the practice of Family Takaful for producing the sale illustration product which Shariah compliant. The study develops a new model of the premium for an equity-linked policy (Unit-linked product) by considering the properties of Takaful contracts namely Tabarru and Mudarabah. It aims to ensure that a new model developed can comprehensively demonstrate Shariah compliance. The model adapted and derived from the current Takaful Business Model. We add several assumptions to implicate the approach in a real problem associated with the ratio of profit-sharing (Mudarabah) and loss-sharing (Tabarru). Secondary data are used to test and produce a sales illustration product by utilising a new integrated model of the premium developed. Based on the empirical results, a new model of premium is used to create a sales illustration product that comprehensively complies with Shariah and also more profitable and beneficial when compared with a standard approach used by Takaful operator.

The increase in economic activity in the industrial sector and the rapid growth of the world population have stimulated an increase in energy demand. In 2004, Indonesia earned the status of a net importer of oil so that it becomes a challenge for the Indonesian government in developing the use of renewable energy to achieve ideal conditions for national energy security. Indonesia has the potential for large amounts of renewable energy sources, one of which is palm-based biodiesel. The mandatory biodiesel policy program was implemented in 2008 with a biodiesel content of 2.5% and gradually until 2019 with a biodiesel content of 30% (B30). The mandatory biodiesel policy is closely related to the achievement of the Sustainable Development Goals (SDGs), and the concept of maintaining the balance of Trilemma Energi. The current energy management and utilization policies in Indonesia continue to increase in line with modern life consumption patterns that require a more environmentally friendly energy variable for energy absorption in Indonesia, especially renewable energy. The purpose of this research is to determine the integration model of palm-based biodiesel policy as a renewable energy commodity to support energy security. This study uses several strategic frameworks by combining a quantitative approach through the perspective of the Balanced Scorecard (BSC) and measuring the technology coefficient using the Technology Contribution Coefficient (TCC), as well as a qualitative approach with the Business Model Canvas (BMC) and the design of the Omnibus Law. Data were collected through Focus Group Discussion (FGD) and Expert Opinion (EO) which were validated by Structural Equation Modeling-Partial Least Square (SEM-PLS) using a sample of 40 respondents from related agencies. The results showed that based on the SEM-PLS validation of 20 BSC perspective variables, two invalid variables were obtained, namely the variable efficiency port service cost and value-added creation which had a P value> 0.05. Meanwhile, Indonesia's TCC score is quite high, namely 0.787, which means that Indonesia is quite aggressive in developing biodiesel and its policies. Based on the results of the FGD expert, it was obtained that the BMC initiates the helicopters to view current biodiesel developments. And 10 regulations have been drafted into a proposed draft Omnibus Law through an action plan.

Gamification as a new concept uses game elements in a novel way to engage users of a non-gaming system and can be used in many domains within an enterprise, to implement the organizational processes with lower costs, higher quality or in a more efficient way. Although there are many researches on gamification but a few studies can be found in the organizational gamification and there are few research works about framework and methodology for designing and implementing organizational gamification in the literature. The purpose of this article is to provide a comprehensive methodology for the enterprise gamification. This research is an attempt to overcome the mentioned gap via presenting a methodology by applying some important issues including organizational, humanity and gamification aspects together to design and implement customized enterprise gamification solutions through reviewing the related literature and experts’ commentaries. The evaluation of the methodology showed that it is an appropriate and perfect way to design gamification solutions in an organization, besides the enterprise needs to provide the necessary conditions for its implementation. This paper forwards an important debate on a comprehensive methodology for applying enterprise gamification, which explains how to properly use gamification in enterprises to increase productivity and better communication with employees, and thus contributes to literature on internal and enterprise gamification.

The study proposes a set of enablers of the consumer sustainable organic food consumption and detects the interrelationship between these attributes. This paper adopts the fuzzy set theory and decision-making trial and evaluation to explore the interrelationship between attributes, including consumer demographic aspect, psychological aspect, social-level aspect and stakeholder impact being explained through 13 criteria and being assessed by experts in the industry. The findings show that stakeholder impact and demographic aspect belong to a causal group and impact the other two aspects. The six most important attributes affecting sustainable consumption of organic foods are support and guidance from government support, mass media, education and research institutions, educational level, income status and consumer age. The study grants an alternative approach for sustainable consumption theory through providing a fuzzy-set theory for multiple criteria decisions making in sustainable consumption of organic foo

The healthcare system is a vital element for any community, as it extremely affects the socio-economic development of any country. The current study aims to assess the performance of the healthcare systems of the countries above fifty million citizens in facing the spread of the COVID-19 pandemic since late December 2019. For this purpose, seven scenarios were adopted via the DEA methodology with six variables, which are the number of medical practitioners (doctors and nurses), hospital beds, Conducted Covid-19 tests, affected cases, recovered cases, and death cases. To shed light on the relative efficiency of drivers, the Tobit analysis was used. Besides, the study carried out various statistical tests for the DEA models' findings to validate the choice of the variables and the obtained scores. The DEA results reveal that less than half of the considered countries are relatively efficient. Moreover, the Tobit regression analysis showed that the main impact on the efficiency scores was due to the number of affected and recovered cases. Finally, the results of the tests of Spearman, Mann-Whitney U, and Kruskal-Wallis H indicate the internal validity and robustness of the chosen DEA models. The current study findings raise important implications, which can be helpful for decision makers regarding continuous improvement of performance, in which the findings assert the importance of achieving the best practices regarding relative efficiency through the linkage between the healthcare systems’ resources, and the needed outputs.

Flow shop scheduling problems with rudimentary criteria of minimum makespan are the most important investigated problems in the field of scheduling. Generally during the process of generating an optimal sequence, multiple partial sequences claiming the optimal value of makespan are observed. In this paper a novel tie-breaking rule to select one of the best optimal sequences out of all possible partial sequences is developed which then applied to Nawaz-Enscore-Ham (NEH) heuristic to solve the scheduling problems in permutation flowshop without increasing the computational complexity. The performance of proposed heuristic is tested with other existing tie-breaking heuristics of similar complexity over Taillard and VRF's instances. Computational results reveal that in terms of solution quality, the proposed heuristic outperforms over the other NEH based heuristics of the same complexity reported in literature.