| 31. |
- Barrera Diaz, Carlos Alberto, 1987-, et al.
(författare)
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An Enhanced Simulation-Based Multi-Objective Optimization Approach with Knowledge Discovery for Reconfigurable Manufacturing Systems
- 2023
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Ingår i: Mathematics. - : MDPI. - 2227-7390. ; 11:6
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Tidskriftsartikel (refereegranskat)abstract
- In today’s uncertain and competitive market, where manufacturing enterprises are subjected to increasingly shortened product lifecycles and frequent volume changes, reconfigurable manufacturing system (RMS) applications play significant roles in the success of the manufacturing industry. Despite the advantages offered by RMSs, achieving high efficiency constitutes a challenging task for stakeholders and decision makers when they face the trade-off decisions inherent in these complex systems. This study addresses work task and resource allocations to workstations together with buffer capacity allocation in an RMS. The aim is to simultaneously maximize throughput and to minimize total buffer capacity under fluctuating production volumes and capacity changes while considering the stochastic behavior of the system. An enhanced simulation-based multi-objective optimization (SMO) approach with customized simulation and optimization components is proposed to address the abovementioned challenges. Apart from presenting the optimal solutions subject to volume and capacity changes, the proposed approach supports decision makers with knowledge discovery to further understand RMS design. In particular, this study presents a customized SMO approach combined with a novel flexible pattern mining method for optimizing an RMS and conducts post-optimal analyses. To this extent, this study demonstrates the benefits of applying SMO and knowledge discovery methods for fast decision support and production planning of an RMS.
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| 32. |
- Barrera Diaz, Carlos Alberto, 1987-, et al.
(författare)
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Optimizing Reconfigurable Manufacturing Systems for Fluctuating Production Volumes : A Simulation-Based Multi-Objective Approach
- 2021
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Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 9, s. 144195-144210
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Tidskriftsartikel (refereegranskat)abstract
- In today's global and volatile market, manufacturing enterprises are subjected to intense global competition, increasingly shortened product lifecycles and increased product customization and tailoring while being pressured to maintain a high degree of cost-efficiency. As a consequence, production organizations are required to introduce more new product models and variants into existing production setups, leading to more frequent ramp-up and ramp-down scenarios when transitioning from an outgoing product to a new one. In order to cope with such as challenge, the setup of the production systems needs to shift towards reconfigurable manufacturing systems (RMS), making production capable of changing its function and capacity according to the product and customer demand. Consequently, this study presents a simulation-based multi-objective optimization approach for system re-configuration of multi-part flow lines subjected to scalable capacities, which addresses the assignment of the tasks to workstations and buffer allocation for simultaneously maximizing throughput and minimizing total buffer capacity to cope with fluctuating production volumes. To this extent, the results from the study demonstrate the benefits that decision-makers could gain, particularly when they face trade-off decisions inherent in today's manufacturing industry by adopting a Simulation-Based Multi-Objective Optimization (SMO) approach.
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| 33. |
- Beheshtinia, Mohammad Ali, et al.
(författare)
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Energy‐efficient and sustainable supply chain in the manufacturing industry
- 2023
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Ingår i: Energy Science & Engineering. - : John Wiley & Sons. - 2050-0505. ; 11:1, s. 357-382
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Tidskriftsartikel (refereegranskat)abstract
- This study aims at reducing energy consumption in supply chain networks by providing optimal integrated production and transportation scheduling. The considered supply chain consists of one main manufacturing center, multiple production units (i.e., suppliers), and multiple heterogeneous vehicles as the transportation fleet. To schedule this complex supply chain network in an energy-efficient way, several decisions should be made concerning the assignment of orders to suppliers and determining their production sequence, splitting orders, assigning orders to vehicles, and assigning delivery priority to orders. To cope with the problem, a mixed-integer linear programming model is presented. Due to the complexity of the problem, a novel development of the genetic algorithm named the Multiple Reference Group Genetic Algorithm (MRGGA) is also proposed. Four objectives are considered to be optimized to meet both suitability and energy-efficiency aspects in the supply chain network. These optimization objectives are to minimize the total orders' delivery times to the manufacturing center, fuel consumption by the vehicles, energy consumption at supplies, and maximize orders' quality. To analyze the performance of the proposed algorithm, a real case and a set of generated instances are solved. The results obtained by the proposed algorithm are compared with an existing genetic algorithm in the literature. Moreover, the results are also compared with the optimal solutions obtained from the mathematical model for small-size problems. The results of the comparisons show the efficiency of the proposed MRGGA in finding energy-efficient solutions for the considered supply chain network.
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| 34. |
- Beheshtinia, Mohammad Ali, et al.
(författare)
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Evaluating and prioritizing the healthcare waste disposal center locations using a hybrid multi-criteria decision-making method
- 2023
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Healthcare waste disposal center location (HCWDCL) impacts the environment and the health of living beings. Different and sometimes contradictory criteria in determining the appropriate site location for disposing of healthcare waste (HCW) complicate the decision-making process. This research presents a hybrid multi-criteria decision-making (MCDM) method, named PROMSIS, to determine the appropriate HCWDCL in a real case. The PROMSIS is the combination of two well-known MCDM methods, namely TOPSIS and PROMETHEE. Moreover, fuzzy theory is used to describe the uncertainties of the problem parameters. To provide a reliable decision on selecting the best HCWDCL, a comprehensive list of criteria is identified through a literature review and experts’ opinions obtained from the case study. In total, 40 criteria are identified and classified into five major criteria, namely economic, environmental, social, technical, and geological. The weight of the considered criteria is determined by the Analytical Hierarchy Process (AHP) method. Then, the score of the alternative HCWDCLs in each considered criterion is obtained. Finally, the candidate locations for disposing of HCWs are ranked by the proposed fuzzy PROMSIS method. The results show that the most important criteria in ranking the alternatives in the studied case are economic, environmental, and social, respectively. Moreover, the sub-criteria of operating cost, transportation cost, and pollution are identified as the most important sub-criteria, respectively.
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| 35. |
- Beheshtinia, Mohammad Ali, et al.
(författare)
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Identifying and prioritizing marketing strategies for the building energy management systems using a hybrid fuzzy MCDM technique
- 2023
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Ingår i: Energy Science & Engineering. - : John Wiley & Sons. - 2050-0505. ; 11:11, s. 4324-4348
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Tidskriftsartikel (refereegranskat)abstract
- Preventing energy waste in residential and office buildings has emerged as a critical issue in both developed and developing countries over recent decades. The growing demand for oil and energy reserves has amplified the urgency of this concern. The deployment of building energy management systems (BEMSs) can lead to timely responses to changes in environmental conditions, the prevention of energy wastage, a reduction in CO2 emissions, and an increase in the longevity of building equipment. Despite the undeniable benefits of BEMSs, their market size remains small, creating challenges for providers in reaching potential customers. This research seeks to identify and prioritize the marketing strategies for BEMSs. A case study was conducted, employing the “Strengths, Weaknesses, Opportunities, and Threats” analysis as a tool for identifying marketing strategies related to BEMSs. This method resulted in the identification of 18 distinct marketing strategies. These strategies were subsequently prioritized using a novel fuzzy multicriteria decision-making technique, VIkor-topSIS, considering six specific criteria. The findings of the study suggested a hierarchical influence of six criteria on the BEMS market, arranged in the following order of significance: effectiveness, cost, attainability, complexity, timing, and popularity. Furthermore, the top three marketing strategies for BEMSs were found to be internet advertising strategies, discounts to consumers, and online sales. The analysis of the results has also offered valuable insights into the strengths and weaknesses of the studied BEMS provider, as well as the opportunities and threats present within the BEMS market.
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| 36. |
- Beheshtinia, Mohammad Ali, et al.
(författare)
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Optimizing disaster relief goods distribution and transportation : a mathematical model and metaheuristic algorithms
- 2023
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Ingår i: APPLIED MATHEMATICS IN SCIENCE AND ENGINEERING. - : TAYLOR & FRANCIS LTD. - 2769-0911. ; 31:1
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Tidskriftsartikel (refereegranskat)abstract
- The effective distribution of relief goods is critical in mitigating the impact of natural disasters and preserving human life. This study addresses a relief goods distribution problem, assuming the existence of multiple relief orders that must be delivered to various disaster-stricken regions from a network of warehouses using a fleet of diverse vehicles. The objective is to identify the most suitable warehouse for each relief order, allocate relief orders to vehicles, batch the orders in the designated vehicles, and devise routing plans to minimize the total delivery time. A mixed-integer linear programming model is formulated to tackle this problem. Owing to the problem's NP-hard nature, a metaheuristic algorithm, known as the Multiple League Championship Algorithm, is developed. Furthermore, two innovative variants of the MLCA , namely the League Base Multiple League Championship Algorithm (L- MLCA) and the Playoff Multiple League Championship Algorithm (P-MLCA), are introduced.Experimental results indicate that the P-MLCA outperforms the other two algorithms. The solutions derived from the P-MLCA are compared with the optimal solutions obtained by a commercial solver for small-scale problems. This comparative analysis demonstrates the promising performance of the P-MLCA in finding the optimal distribution of relief goods.
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| 37. |
- Beheshtinia, Mohammad Ali, et al.
(författare)
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Prioritizing healthcare waste disposal methods considering environmental health using an enhanced multi-criteria decision-making method
- 2023
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Ingår i: Environmental Pollutants and Bioavailability. - : Taylor & Francis Group. - 2639-5932 .- 2639-5940. ; 35:1, s. 250-269
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Tidskriftsartikel (refereegranskat)abstract
- The Healthcare Waste Disposal Method Selection (HCWDMS) is a complicated problem due to multiple and often contradictory criteria with different importance degrees. Thus, decision-makers are restored to multi-criteria decision-making (MCDM) methods to prioritize and select the best HCW disposal methods. This study introduces an enhanced MCDM method to deal with the HCWDMS problem. To address the problem, a comprehensive list of criteria and HCW disposal methods are identified. All the criteria are categorized into four main criteria, and Fuzzy Analysis Hierarchy Process is used to determine the weights of considered criteria and sub-criteria. The study results show that environmental, economic, technical, and social criteria are the most important in selecting disposal methods, respectively. Moreover, the sub-criteria of ‘Health Risk’, ‘Release with health effects’, and ‘Capital cost’ have the highest importance, respectively. Additionally, the methods of ‘Microwave’, ‘Sterilization by autoclave’, and ‘Reverse polymerization’ have the highest priority, respectively.
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| 38. |
- Beheshtinia, Mohammad Ali, et al.
(författare)
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Supply Chain Optimization Considering Sustainability Aspects
- 2021
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 13:21, s. 1-23
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Tidskriftsartikel (refereegranskat)abstract
- Supply chain optimization concerns the improvement of the performance and efficiency of the manufacturing and distribution supply chain by making the best use of resources. In the context of supply chain optimization, scheduling has always been a challenging task for experts, especially when considering a distributed manufacturing system (DMS). The present study aims to tackle the supply chain scheduling problem in a DMS while considering two essential sustainability aspects, namely environmental and economic. The economic aspect is addressed by optimizing the total delivery time of order, transportation cost, and production cost while optimizing environmental pollution and the quality of products contribute to the environmental aspect. To cope with the problem, it is mathematically formulated as a mixed-integer linear programming (MILP) model. Due to the complexity of the problem, an improved genetic algorithm (GA) named GA-TOPKOR is proposed. The algorithm is a combination of GA and TOPKOR, which is one of the multi-criteria decision-making techniques. To assess the efficiency of GA-TOPKOR, it is applied to a real-life case study and a set of test problems. The solutions obtained by the algorithm are compared against the traditional GA and the optimum solutions obtained from the MILP model. The results of comparisons collectively show the efficiency of the GA-TOPKOR. Analysis of results also revealed that using the TOPKOR technique in the selection operator of GA significantly improves its performance.
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| 39. |
- Billing, Erik, 1981-, et al.
(författare)
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Expectations of robot technology in welfare
- 2019
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Konferensbidrag (refereegranskat)abstract
- We report findings from a survey on expectations of robot technology in welfare, within the coming 20 years. 34 assistant nurses answered a questionnaire on which tasks, from their daily work, that they believe robots can perform, already today or in the near future. Additionally, the Negative attitudes toward robots scale (NARS) was used to estimate participants' attitudes towards robots in general. Results reveal high expectations of robots, where at least half of the participants answered Already today or Within 10 years to 9 out of 10 investigated tasks. Participants were also fairly positive towards robots, reporting low scores on NARS. The obtained results can be interpreted as a serious over-estimation of what robots will be able to do in the near future, but also large varieties in participants' interpretation of what robots are. We identify challenges in communicating both excitement towards a technology in rapid development and realistic limitations of this technology.
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| 40. |
- Binder, Pauline, 1965-, et al.
(författare)
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Hi-TENS combined with PCA-morphine as post caesarean pain relief
- 2011
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Ingår i: Midwifery. - : Elsevier. - 0266-6138 .- 1532-3099. ; 27:4, s. 547-552
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: to examine effectiveness and overall opiate consumption between high-sensory transcutaneous electrical nerve stimulation (Hi-TENS) combined with patient-controlled analgesia with morphine and patient-controlled analgesia with morphine alone following elective (e.g. scheduled) caesarean birth. Design: randomised, controlled study. Setting: a county hospital in south-west Sweden. Participants: 42 multiparous women. Measurements and findings: participants were randomly assigned and connected to patient-controlled analgesia with morphine alone or in combination with Hi-TENS apparatus. Levels of morphine consumed were calculated every third hour during the first 24 hours post partum. Pain and sedation were assessed by visual analogue scale at one, three, six, nine, 12 and 24 hours post partum. Total consumption of morphine differed significantly between the groups: morphine with TENS was 16.2+/-12.6 mg and morphine alone was 33.1+/-20.9 mg (p = 0.007). Assessment of pain relief showed no significant difference. Sedation differed significantly between the groups (p = 0.045), especially between three and 12 hours post partum (p = 0.011). Key conclusions and implications for practice: pain relief from a combination of Hi-TENS and patient-controlled analgesia with morphine was as effective as patient-controlled analgesia with morphine alone, produced less sedation and reduced morphine use by approximately 50%. Women undergoing a caesarean section should be given the opportunity to make an informed choice about post operative pain relief before surgery. A presumed benefit of this treatment combination is that the mother is more alert and better able to interact with her newborn during the first hours after birth without drowsiness due to large doses of opiates.
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