Uncertainties in the resource conservation problems: a review View Full Text


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Article Info

DATE

2022-07-12

AUTHORS

Deepika Arya, Santanu Bandyopadhyay

ABSTRACT

Process integration, which started its development in the early 1970s, is an emerging branch of study for conserving various resources. Process integration studies the interdependencies among various process units at the system level and the development and use of tools for holistically designing process networks with generic optimization of resources and sustainable development. The problems addressed in process integration are often referred to as resource conservation or source–sink allocation problems. Most of these problems are solved with precise input parameters. However, due to a wide range of known and unknown factors, these input parameters are uncertain in practical applications. To make the designed network more reliable, these uncertainties should be incorporated at the targeting stage of the problem. Over the years, researchers have used various approaches for managing resource conservation networks under uncertainty. This review examines the different mathematical optimization approaches adopted for handling uncertainties associated with the resource conservation networks along with their practical applications in recent years. The paper primarily examines the four most common approaches used to address uncertainties in process integration: sensitivity analysis, chance-constrained programming, fuzzy optimization, and interval programming. Recent advances in handling uncertainties within the framework of process integration, covering both mathematical programming and Pinch analysis, are also discussed. The review ends with a discussion on the significance and contributions of recent approaches. Some of the important future research directions are also identified to be addressed using process integration and Pinch analysis.Graphical abstract More... »

PAGES

1-19

References to SciGraph publications

  • 2017-09-27. Pinch Analysis as a Quantitative Decision Framework for Determining Gaps in Health Care Delivery Systems in PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY
  • 2021-04-14. Assessing the Reliability of Integrated Bioenergy Systems to Capacity Disruptions via Monte Carlo Simulation in PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY
  • 2020-07-11. Pinch analysis to reduce fire susceptibility by redeveloping urban built forms in CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
  • 2022-01-18. Economic Pinch Analysis for Estimating Service Life in PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY
  • 2007-01-01. A Simple Model for Assessing Output Uncertainty in Stochastic Simulation Systems in MICAI 2007: ADVANCES IN ARTIFICIAL INTELLIGENCE
  • 2012-11-27. How to determine basis stability in interval linear programming in OPTIMIZATION LETTERS
  • 2012-08-07. The optimal solution set of the interval linear programming problems in OPTIMIZATION LETTERS
  • 2002-06-07. Process integration design methods for water conservation and wastewater reduction in industry. Part 3: Experience of industrial application in CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
  • 2000-02-18. Linear programming with interval coefficients in JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
  • 2017-09-18. An improved risk-explicit interval linear programming model for pollution load allocation for watershed management in ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
  • 2020-11-17. Optimal Design of Biomass Combined Heat and Power System Using Fuzzy Multi-Objective Optimisation: Considering System Flexibility, Reliability, and Cost in PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY
  • 1981-03. Strong solvability of interval linear programming problems in COMPUTING
  • 2015-11-30. Convex contractive interval linear programming for resources and environmental systems management in STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
  • 2018-02-08. Solving methods for interval linear programming problem: a review and an improved method in OPERATIONAL RESEARCH
  • 2021-06-08. A fuzzy optimization model for planning integrated terrestrial carbon management networks in CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
  • 2017-06-30. Integrated grey relational analysis and multi objective grey linear programming for sustainable electricity generation planning in ANNALS OF OPERATIONS RESEARCH
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