Disaster Management Cycle-Based Integrated Humanitarian Supply Network Management

While logistics research recently has placed increased focus on disruptionmanagement, few studies have examined the response and recovery phases in post-disaster operations. We present a multiple-objective, integrated network optimizationmodel for making strategic decisions in the supply distribution and network restorationphases of humanitarian logistics operations. Our model provides an equity- or fairness-based solution for constrained capacity, budget, and resource problems in post-disasterlogistics management. We then generate efficient Pareto frontiers to understand the trade-off between the objectives of interest.Next, we present a goal programming-based multiple-objective integratedresponse and recovery model. The model prescribes fairness-based compromise solutionsfor user-desired goals, given limited capacity, budget, and available resources. Anexperimental study demonstrates how different decision making strategies can beformulated to understand important dimensions of decision making.Considering multiple, conflicting objectives of the model, generating Pareto-optimal front with ample, diverse solutions quickly is important for a decision maker tomake a final decision. Thus, we adapt the well-known Non-dominated Sorting GeneticAlgorithm II (NSGA-II) by integrating an evolutionary heuristic with optimization-basedtechniques called the Hybrid NSGA-II for this NP-hard problem. A Hypervolume-basedtechnique is used to assess the algorithm’s effectiveness. The Hazards U.S. Multi-Hazard(Hazus)-generated regional case studies based on earthquake scenarios are used todemonstrate the applicability of our proposed models in post-disaster operations

Multiple-Objective Analysis of Integrated Relief Distribution and Network Restoration in Post-Disaster Humanitarian Logistics - Hazus based South Carolina (SC) Case Study

In this research, motivated by the 2004 Asian Tsunami, we focus on a large-scale supply network problem during a disaster, known as humanitarian logistics or supply disruption. This is an emerging research domain gaining recent attention from several research communities. While several works exist in the pre-disaster operations, there is a clear need for research in post-disaster operations. Thus, several issues arise during a post-disaster, such as relief supply distribution and network restoration, are integrated and studied through Operations Research techniques, inclusive of multiple-criteria programming, goal programming, metaheuristics, etc. The poster shows the Multiple-Objective Integrated Response and Recovery (MOIRR) model, which provides an equity- or fairness-based solution for constrained capacity, budget, and resource problems in post-disaster logistics management. Further, a designed experiment for this NP-hard problem is conducted to analyze important aspects of the integrated problem for both small- and large-sized networks: full vs. partial restoration and pooled vs. separate budgeting approaches. Finally, the model is applied to a Hazus-generated regional case study in South Carolina (SC) based on an earthquake scenario and efficient Pareto frontiers are generated to understand the trade-off between the objectives of interest

A Decision-Support Model for Additive Manufacturing Scheduling Using an Integrative Analytic Hierarchy Process and Multi-Objective Optimization

Additive manufacturing (AM) became widespread through several organizations due to its benefits in providing design freedom, inventory improvement, cost reduction, and supply chain design. Process planning in AM involving various AM technologies is also complicated and scarce. Thus, this study proposed a decision-support tool that integrates production and distribution planning in AM involving material extrusion (ME), stereolithography (SLA), and selective laser sintering (SLS). A multi-objective optimization approach was used to schedule component batches to a network of AM printers. Next, the analytic hierarchy process (AHP) technique was used to analyze trade-offs among conflicting criteria. The developed model was then demonstrated in a decision-support system environment to enhance practitioners' applications. Then, the developed model was verified through a case study using automotive and healthcare parts. Finally, an experimental design was conducted to evaluate the complexity of the model and computation time by varying the number of parts, printer types, and distribution locations

Multicriteria decision analysis framework for part orientation analysis in additive manufacturing

Additive manufacturing (AM) or three-dimensional printing (3DP) refers to producing objects from digital information layer by layer. Despite recent advancements in AM, process planning in AM has not received much attention compared to subtractive manufacturing. One of the critical process planning issues in AM is deciding part orientation. In this research, the integrative framework of multicriteria decision making for part orientation analysis in AM is investigated. Initially, quantitative data are assessed using the data envelopment analysis (DEA) technique without preferences from a decision maker. In contrast, a decision maker's preferences are qualitatively analysed using the analytic hierarchy process (AHP) technique. Then, the proposed framework combining explicit data as in DEA, implicit preference as in AHP, and linear normalization (LN) technique is used, which reflects both preference and objective data in supporting decision making for 3DP part orientation. Two particular AM technologies, namely Fused Deposition Modelling and Selective Laser Sintering, are used as a case study to illustrate the proposed algorithm, which is further verified with experts to improve process planning for AM

A Highway-Driving System Design Viewpoint using an Agent-based Modeling of an Affordance-based Finite State Automata

This paper presents an agent-based modeling framework for affordance-based driving behaviors during the exit maneuver of driver agents in human-integrated transportation problems. We start our discussion from one novel modeling framework based on the concept of affordance called the Affordance-based Finite State Automata (AFSA) model, which incorporates the human perception of resource availability and action capability. Then, the agent-based simulation illustrates the validity of the AFSA framework for the Highway-Lane-Driver System. Next, the comparative study between real driving data and agent-based simulation outputs is provided using the transition diagram. Finally, we perform a statistical analysis and a correlation study to analyze affordance-based driving behavior of driver agents. The simulation results show that the AFSA model well represents the perception-based human actions and drivers??? characteristics, which are essential for the design viewpoint of control framework of human driver modeling. This study is also expected to benefit a designed control for autonomous/self-driving car in the future

การใช้เครื่องมือการทำการตัดสินใจแบบหลายปัจจัยในการแก้ปัญหาทิศทางการผลิตชิ้นงานจากการผลิตแบบดั้งเดิมและแบบพิมพ์สามมิติMulti-Criteria Decision Analysis-based Orientation Selection Problem for Integrated 3D Printing and Subtractive Manufacturing

งานวิจัยนี้เป็นการศึกษาปัญหาทิศทางการผลิตชิ้นงานจากกระบวนการผลิตด้วยเทคโนโลยีแบบดั้งเดิมและแบบพิมพ์สามมิติโดยเป็นการเปรียบเทียบระหว่างการใช้เครื่องพิมพ์สามมิติแบบหัวฉีด Fused Deposition Modeling (FDM) เครื่องพิมพ์สามมิติแบบฉายแสง Stereolithography (SLA) และเครื่องกลึงในการผลิตชิ้นงานประกอบ โดยวัสดุที่ใช้สำหรับเครื่อง FDM คือพลาสติก Acrylonitrile-Butadiene-Styrene (ABS) และพลาสติก Polylactic Acid (PLA) ส่วนวัสดุที่ใช้กับเครื่อง SLA คือ เรซิ่นและวัสดุเครื่องกลึงคือแท่งพลาสติก ABS โดยทำการผลิตชิ้นงาน 4 แนวในทิศทาง 0 องศา 45 องศา 90 องศา และ 180 องศาตามลำดับ และเก็บข้อมูลปัจจัยการผลิตคือปริมาณวัสดุ เวลาในการผลิต ต้นทุนการผลิต ของเสียจากวัสดุสนับสนุน ความแม่นยำของชิ้นงาน การประกอบ และคุณภาพผิวสำเร็จ จากนั้นใช้เครื่องมือการทำการตัดสินใจแบบหลายปัจจัยในการวิเคราะห์ข้อมูล โดยเริ่มจากการวิเคราะห์ประสิทธิภาพด้วยวิธีการวิเคราะห์แบบล้อมกรอบข้อมูล (Data Envelopment Analysis: DEA) สำหรับแต่ละกลุ่มเทคโนโลยีการผลิตและประเภทวัสดุ จากนั้นใช้กระบวนการลำดับชั้นเชิงวิเคราะห์ (Analytic Hierarchy Process: AHP) เพื่อหาค่านํ้าหนักของแต่ละปัจจัยตามความต้องการของแต่ละผู้ตัดสินใจ และทำการนอร์มัลไลเซชันเชิงเส้นตรง (Linear Normalization) เพื่อเป็นตัวชี้วัดในการหาการผลิตชิ้นงานที่ดีที่สุด โดยพบว่าชิ้นงานที่ผลิตในแนว 0 องศาเป็นชิ้นงานที่เหมาะสมที่สุด โดยมีจุดเด่นในด้านปัจจัยปริมาณวัสดุทีใช้ ต้นทุนในการผลิต และการเกิดของเสียในการผลิตที่ต่ำที่สุด ซึ่งพบว่ารูปแบบเทคโนโลยีในการผลิตที่แตกต่างกันส่งผลต่อปัจจัยในการผลิตที่แตกต่างกัน และความต้องการของผู้ตัดสินใจในรูปแบบของค่านํ้าหนักของแต่ละปัจจัยส่งผลต่อผลการผลิตชิ้นงานที่ดีที่สุดเช่นกันThis study examines the orientation selection problem for the three-dimensional printing (3DP) and subtractive manufacturing technologies by comparing the 3D Fused Deposition Modeling (FDM), the 3D Stereolithography (SLA), and the lathe machine for assembly part production. Whereas materials used for 3D FDM are Acrylonitrile-Butadiene-Styrene (ABS) and Polylactic Acid (PLA) thermoplastics and material used for 3D SLA is resin; the material used for lathe machine is solid ABS. The orientation directions analyzed for 3DP assembly parts are from 0 degrees, 45 degrees, 90 degrees, and 180 degrees, respectively. Data are then collected for the comparative study from various criteria, which are consumed material, production time, production cost, support material, production accuracy, assembly, and surface quality. Then, we use the multi-criteria decision analysis (MCDA) techniques by starting with the Data Envelopment Analysis (DEA) to analyze the relative efficiency of each manufacturing technology group and each material type. Then, multiple factors are analyzed using the Analytic Hierarchy Process (AHP) to assess the criteria weight based on the preference of a decision-maker. The Linear Normalization analysis is then later used to find the best alternative of orientation direction. The results show that production orientation with 0 degrees provides the best orientation alternative superior in terms of minimal consumed material, production cost, and support material. In addition, dissimilar technologies are found to affect production criteria and preferences from decision-makers are also found to impact how the production alternatives are ranked.Keywordsเทคโนโลยีเครื่องพิมพ์สามมิติ; ปัญหาทิศทางการผลิตชิ้นงาน; การทำการตัดสินใจแบบหลายปัจจัย; วิธีการวิเคราะห์แบบล้อมกรอบข้อมูล; กระบวนการลำดับชั้นเชิงวิเคราะห์; วิธีการนอร์มัลไลเซชันเชิงเส้นตรงThree-Dimensional Printing; Orientation Selection Problem; Multi-Criteria Decision Analysis; Data Envelopment Analysis; Analytic Hierarchy Process; Linear Normalizatio

Criteria Analysis of Food Safety using the Analytic Hierarchy Process (AHP) - A Case study of Thailand’s Fresh Markets

Safety of food in the fresh market has been a critical issue for many countries, including Thailand. In this study, data related to the criteria pertaining to food safety in selected fresh markets in Thailand are collected and analyzed using selective analytical methods to understand the perspectives of stakeholders in food safety system. In particular, our study considered 2 methodologies in the analysis-1) Mixed Method Research based on questionnaires and interviews with an aim to analyze stakeholders’ behaviours and 2) Analytic Hierarchy Process (AHP), one of the Multi Criteria Decision Making (MCDM) tools, with an aim to analyze criteria weights for food safety. Our case study was conducted at two fresh markets in Ubonratchathani province in Thailand: Municipal Market and Donklang Market, by collecting samples of vendors and consumers. It was found that vendors considered rental arrangement as the most important factor with weight 0.5489 (54.8 percent), whereas consumers concerned with the market building and related environment the most with criterion’s weight 0.2480 (24.80 percent). This initial result can be used for further analysis of fresh market layout and design, subject to viewpoints of stakeholders

Data envelopment analysis-based multi-criteria decision making for part orientation selection in fused deposition modeling

Additive manufacturing (AM) has become popular in various fields, not only for industrial use, but also for personal use due to its key advantages in almost unlimited design freedom and material efficiency. Manufacturers in the industry recognize AM as a promising method in direct digital manufacturing for their design, research and development, and production processes. However, the applicability of AM technology is limited due to its process instability from several factors including the orientation selection of the part. Orientation of a part refers to the building direction with respect to the part being fabricated by the AM machine. In addition, available quantitative methods to determine the part orientation are limited. In this paper, we examine the part orientation alternatives' efficiency using data envelopment analysis (DEA). We illustrate a case study for one AM process; fused deposition modeling (FDM). The orientation alternatives' efficiency is identified and presented through trade-offs among conflicting criteria and machines. By using the DEA analysis, it provides insights regarding efficiency of each alternative, which can be used for the benchmarking leading to a best-practice frontier. The proposed method can be applied to other AM technologies in the industrial AM-based production environments for effective management

Relative Efficiency Analysis of Biomass Agricultural Plants using Data Envelopment Analysis

Renewable energy has recently been a promising interest as a substitute for fossil fuels due to an increasing energy demand as well as a rising concern over the environmental impact of fossil fuel consumption around the globe. Biofuel, in particular, is a type of renewable energy, which can be derived from various biomass types. In this research, we analyze relative efficiencies using Data Envelopment Analysis (DEA) technique from three types of energy-related plants in the Northeastern region of Thailand, which are cassava, sugarcane, and palm. The relative efficiency of each province is further analyzed during 2017 to 2019 for a comparative study. Next, the input criteria are collected including allowable planting area, labor cost, and rainfall amount; whereas the included output criterion is the quantity of harvested product. Our initial analysis using CCR, BBC, and Scale Efficiency (SE) models of DEA provides the baseline of efficient provinces to be benchmarked and directions for improving inefficient provinces, given desired input and output criteria in this study

Integrated IEW-TOPSIS and Fire Dynamics Simulation for Agent-Based Evacuation Modeling in Industrial Safety

Emergency events in the industrial sector have been increasingly reported during the past decade. However, studies that focus on emergency evacuation to improve industrial safety are still scarce. Existing evacuation-related studies also lack a perspective of fire assembly point’s analysis. In this research, location of assembly points is analyzed using the multi-criteria decision analysis (MCDA) technique based on the integrated information entropy weight (IEW) and techniques for order preference by similarity to ideal solution (TOPSIS) to support the fire evacuation plan. Next, we propose a novel simulation model that integrates fire dynamics simulation coupled with agent-based evacuation simulation to evaluate the impact of smoke and visibility from fire on evacuee behavior. Factors related to agent and building characteristics are examined for fire perception of evacuees, evacuees with physical disabilities, escape door width, fire location, and occupancy density. Then, the proposed model is applied to a case study of a home appliance factory in Chachoengsao, Thailand. Finally, results for the total evacuation time and the number of remaining occupants are statistically examined to suggest proper evacuation planning