Skip to Main content Skip to Navigation
New interface
Journal articles

Dynamic Waste Management (DWM):Towards an evolutionary decision-making approach

Abstract : To guarantee sustainable and dynamic waste management, the dynamic waste management approach (DWM) suggests an evolutionary new approach that maintains a constant flow towards the most favourable waste treatment processes (facilities) within a system. To that end, DWM is based on the law of conservation of energy, which allows the balancing of a network, while considering the constraints of incoming (h1) and outgoing (h2) loads, as well as the distribution network (ΔH) characteristics. The developed approach lies on the identification of the prioritization index (PI) for waste generators (analogy to h1), a global allocation index for each of the treatment processes (analogy to h2) and the linear index load loss (ΔH) associated with waste transport. To demonstrate the scope of DWM, we outline this approach, and then present an example of its application. The case study shows that the variable monthly waste from the three considered sources is dynamically distributed in priority to the more favourable processes. Moreover, the reserve (stock) helps temporarily store waste in order to ease the global load of the network and favour a constant feeding of the treatment processes. The DWM approach serves as a decision-making tool by evaluating new waste treatment processes, as well as their location and new means of transport for waste.
Document type :
Journal articles
Complete list of metadata

Cited literature [19 references]  Display  Hide  Download
Contributor : Florent Breuil Connect in order to contact the contributor
Submitted on : Friday, January 25, 2013 - 2:39:31 PM
Last modification on : Wednesday, June 24, 2020 - 4:19:08 PM
Long-term archiving on: : Friday, April 26, 2013 - 3:05:09 AM


Files produced by the author(s)



Gabriel Rojo, Mathias Glaus, Robert Hausler, Valérie Laforest, Jacques Bourgois. Dynamic Waste Management (DWM):Towards an evolutionary decision-making approach. Waste Management and Research, 2013, Volume 31 (Issue 12), pp. 1285-1292. ⟨10.1177/0734242X13507306⟩. ⟨emse-00767075⟩



Record views


Files downloads