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Related Concept Videos

Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Optimization Problems01:26

Optimization Problems

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Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
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Hazard Rate01:11

Hazard Rate

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The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
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Area Problem01:26

Area Problem

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Determining the area of a region with straight edges is straightforward, as geometric formulas for rectangles, triangles, and polygons can be applied directly. However, traditional geometric methods are insufficient when a region has a curved boundary, such as the area under a function.fromThe area problem involves finding a systematic way to measure such regions. One approach to solving this problem is through approximation. Instead of attempting to compute the area exactly at the outset, the...
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An Improved Multi-Objective Programming with Augmented ε-Constraint Method for Hazardous Waste Location-Routing

Hao Yu1, Wei Deng Solvang2

  • 1Department of Industrial Engineering, Faculty of Engineering Science and Technology, UiT-The Arctic University of Norway, Narvik 8505, Norway. hao.yu@uit.no.

International Journal of Environmental Research and Public Health
|June 4, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a new model for hazardous waste management, optimizing facility locations and transportation routes. It balances operating costs and risks to residents, considering recycling policies for better environmental outcomes.

Keywords:
augmented ε-constraint methodhazardous waste managementlocation-routing problemmixed integer programmingmulti-objective programming

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Area of Science:

  • Environmental Science
  • Operations Research
  • Industrial Engineering

Background:

  • Hazardous waste management poses significant risks to residents and the environment.
  • Optimizing facility location and routing is crucial for mitigating these risks.

Purpose of the Study:

  • To develop an improved mathematical formulation for hazardous waste location-routing problems.
  • To assist decision-makers in selecting facility locations, treatment technologies, and transportation routes.
  • To account for varying risks associated with different waste types and treatment methods.

Main Methods:

  • A multi-objective mixed integer programming approach.
  • Incorporation of system operating costs and resident risk into objective functions.
  • Introduction of a compensation factor for varying risk levels.
  • Consideration of policy instruments for waste recycling.
  • Utilizing the augmented ε-constraint method to generate a Pareto optimal curve.

Main Results:

  • The developed model effectively integrates facility location, treatment technology selection, and transportation routing.
  • The study quantifies the trade-offs between operating costs and resident risk.
  • The influence of recycling promotion policies on cost and risk is analyzed.

Conclusions:

  • The improved mathematical model provides a comprehensive framework for hazardous waste management.
  • Decision-makers can utilize this model to balance economic factors with environmental and public health concerns.
  • The research highlights the importance of considering waste-specific risks and policy impacts in optimization models.