Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposal

Purpose: Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.Peer Reviewe

A Hybrid Multi-Criteria Analysis Model for Solving the Facility Location–Allocation Problem: a Case Study of Infectious Waste Disposal

Choosing locations for infectious waste disposal (IWD) is one of the most significant issues in hazardous waste management due to the risk imposed on the environment and human life. This risk can be the result of an undesirable location of IWD facilities. In this study a hybrid multi-criteria analysis (Hybrid MCA) model for solving the facility location–allocation (FLA) problem for IWD was developed by combining two objectives: total cost minimization and weight maximization. Based on an actual case of forty-seven hospitals and three candidate municipalities in the northeastern region of Thailand, first, the Fuzzy AHP and Fuzzy TOPSIS techniques were integrated to determine the closeness of the coefficient weights of each candidate municipality. After that, these weights were converted to weighting factors and then these factors were taken into the objective function of the FLA model. The results showed that the Hybrid MCA model can help decision makers to locate disposal centers, hospitals and incinerator size simultaneously. Besides that the model can be extended by incorporating additional selection criteria/objectives. Therefore, it is believed that it can also be useful for addressing other complex problems

Defect reduction for fabric cutting process to produce polo shirts : a case study of garment factory

This research aims to study the factors affecting the crooked fabric cutting and to present the new cutting procedure that complies with the factors affecting the crooked fabric cutting of a case study. The defect in fabric cutting process was crooked fabric making nonconforming product. The cause and effect diagram was utilized to analyze and suggest related factors leading to the problem. It was showed that the number of times of knife sharpening and the number of layers in fabric paving would affect the crooked fabric cutting the design of experiment was applied to determine appropriate the level of these factors. The main factor significantly affected the crooked fabric cutting (p < 0.05) was the number of times of knife sharpening, but the number of layers in fabric paving and interaction between both factors would not significantly affect the crooked fabric cutting. The number of times of knife sharpening in the level 4 had been sharpened twenty times in each cutting round. The least average defective proportion was 0.0173. Then the new cutting procedure would significantly reduce average defective proportion. It could reduce the average number of defective items as 5.74 pieces in each cutting round or 70.52 percents

Solving multi-objective facility location problem using the fuzzy analytical hierarchy process and goal programming: a case study on infectious waste disposal centers

The selection of a suitable location for infectious waste disposal is one of the major problems in waste management. Determining the location of infectious waste disposal centers is a difficult and complex process because it requires combining social and environmental factors that are hard to interpret, and cost factors that require the allocation of resources. Additionally, it depends on several regulations. Based on the actual conditions of a case study, forty hospitals and three candidate municipalities in the sub-Northeast region of Thailand, we considered multiple factors such as infrastructure, geological and social & environmental factors, calculating global priority weights using the fuzzy analytical hierarchy process (FAHP). After that, a new multi-objective facility location problem model which combines FAHP and goal programming (GP), namely the FAHP-GP model, was tested. The proposed model can lead to selecting new suitable locations for infectious waste disposal by considering both total cost and final priority weight objectives. The novelty of the proposed model is the simultaneous combination of relevant factors that are difficult to interpret and cost factors, which require the allocation of resources. Keywords: Multi-objective facility location problem, Fuzzy analytic hierarchy process, Infectious waste disposal center

A Hybrid Multi-Criteria Analysis Model for Solving the Facility LocationâAllocation Problem: A Case Study of Infectious Waste Disposal

Choosing locations for infectious waste disposal (IWD) is one of the most significant issues in hazardous waste management due to the risk imposed on the environment and human life. This risk can be the result of an undesirable location of IWD facilities. In this study a hybrid multi-criteria analysis (Hybrid MCA) model for solving the facility locationâallocation (FLA) problem for IWD was developed by combining two objectives: total cost minimization and weight maximization. Based on an actual case of forty-seven hospitals and three candidate municipalities in the northeastern region of Thailand, first, the Fuzzy AHP and Fuzzy TOPSIS techniques were integrated to determine the closeness of the coefficient weights of each candidate municipality. After that, these weights were converted to weighting factors and then these factors were taken into the objective function of the FLA model. The results showed that the Hybrid MCA model can help decision makers to locate disposal centers, hospitals and incinerator size simultaneously. Besides that the model can be extended by incorporating additional selection criteria/objectives. Therefore, it is believed that it can also be useful for addressing other complex problems

Solving the Vehicle Routing Problems with Time Windows Using Hybrid Genetic Algorithm with Push Forward Insertion Heuristic and Local Search Procedure

ปัญหาการจัดเส้นทางการขนส่งแบบมีกรอบเวลา (Vehicle Routing Problem with Time Window; VRPTW) เป็นส่วนขยายของปัญหาการจัดเส้นทางการขนส่ง (Vehicle Routing Problem; VRP) ที่มีการเพิ่มข้อจำกัดด้านกรอบเวลาเข้าในตัวแบบทางคณิตศาสตร์ VRP แบบดั้งเดิม ปัญหา VRPTW เป็นปัญหาแบบเอ็นพี-ฮาร์ด (NP-hard) ด้วยเหตุนี้การใช้เทคนิคแบบแม่นตรง (Exact Optimization Techniques) เพื่อที่จะหาคำตอบที่ดีที่สุดสำหรับปัญหา VRPTW จะมีความยุ่งยากเมื่อปัญหามีขนาดใหญ่ ดังนั้นในงานวิจัยนี้จึงเป็นการนำเสนออัลกอริทึมเชิงพันธุกรรมแบบผสมผสาน (hybrid Genetic Algorithm; hybrid GA) สำหรับการแก้ปัญหา VRPTWs ซึ่งอัลกอริทึม hybrid GA เป็นการบูรณาการระหว่างฮิวริสติกแบบแทรกไปข้างหน้า (Push Forward Insertion Heuristic; PFIH) วิธีเชิงพันธุกรรม (Genetic Algorithm; GA) และการค้นหาคำตอบเฉพาะที่จำนวน 3 วิธี (Three Local Searches) โดยที่ PFIH จะถูกนำมาใช้สำหรับการสร้างคำตอบเริ่มต้น (Initial Population) แทนที่การสุ่มของวิธีเชิงพันธุกรรมแบบดั้งเดิม ส่วนการค้นหาคำตอบเฉพาะที่ทั้ง 3 วิธี จะใช้ในขั้นตอนการปรับปรุงคำตอบให้ดียิ่งขึ้น จากนั้นอัลกอริทึมที่นำเสนอได้ถูกนำไปทดสอบประสิทธิภาพกับปัญหามาตรฐานจำนวน 14 ปัญหา โดยการสุ่มจาก 56 ปัญหา ของ Solomon ผลการศึกษาแสดงให้เห็นว่าอัลกอริทึมที่นำเสนอมีประสิทธิภาพในการหาคำตอบที่ดีเมื่อเปรียบเทียบกับปัญหามาตรฐานเหล่านี้The Vehicle Routing Problem with Time Windows (VRPTW) is a kind of important variant of VRP with adding time windows constraints to the model. The VRPTW is classified as an NP-hard problem. Hence, the use of exact optimization techniques may be hard to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. To solve this problem, this paper suggests a hybrid genetic algorithm (hybrid GA) combined with Push Forward Insertion Heuristic (PFIH) to make an initial solution instead of traditional GA and three local searches to neighborhood search and improving method. The proposed algorithm was tested on fourteen instances from an online data set in the Solomon`s 56 benchmark problems-selected randomly. The results indicate the good quality of the proposed algorithm