A Simulated Annealing Algorithm for Solving a Routing Problem in the Context of Municipal Solid Waste Collection

2021 ◽  
pp. 63-76
Author(s):  
Matías Fermani ◽  
Diego Gabriel Rossit ◽  
Adrián Toncovich
Keyword(s):  
Simulated Annealing ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Simulated Annealing Algorithm ◽  
Waste Collection ◽  
Solid Waste Collection ◽  
Routing Problem ◽  
Annealing Algorithm

Strategic waste management planning – the organization of municipal solid waste collection in Oulu, Finland*

2015 ◽  
Vol 10 (2) ◽  
pp. 145-156 ◽  
Author(s):  
Sari Piippo ◽  
Paula Saavalainen ◽  
Juhani Kaakinen ◽  
Eva Pongrácz
Keyword(s):  
Waste Management ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Waste Collection ◽  
Solid Waste Collection ◽  
Management Planning

scholarly journals A Two-Stage Simulated Annealing Algorithm for the Many-to-Many Milk-Run Routing Problem with Pipeline Inventory Cost

2015 ◽  
Vol 2015 ◽  
pp. 1-22 ◽  
Author(s):  
Yu Lin ◽  
Zheyong Bian ◽  
Shujing Sun ◽  
Tianyi Xu
Keyword(s):  
Simulated Annealing ◽  
Heuristic Algorithm ◽  
Simulated Annealing Algorithm ◽  
Greedy Heuristic ◽  
Two Stage ◽  
Satisfactory Solution ◽  
Routing Problem ◽  
Annealing Algorithm ◽  
The Many ◽  
Milk Run

In recent years, logistics systems with multiple suppliers and plants in neighboring regions have been flourishing worldwide. However, high logistics costs remain a problem for such systems due to lack of information sharing and cooperation. This paper proposes an extended mathematical model that minimizes transportation and pipeline inventory costs via the many-to-many Milk-run routing mode. Because the problem is NP hard, a two-stage heuristic algorithm is developed by comprehensively considering its characteristics. More specifically, an initial satisfactory solution is generated in the first stage through a greedy heuristic algorithm to minimize the total number of vehicle service nodes and the best insertion heuristic algorithm to determine each vehicle’s route. Then, a simulated annealing algorithm (SA) with limited search scope is used to improve the initial satisfactory solution. Thirty numerical examples are employed to test the proposed algorithms. The experiment results demonstrate the effectiveness of this algorithm. Further, the superiority of the many-to-many transportation mode over other modes is demonstrated via two case studies.

GIS-Based tools for optimizing municipal solid waste collection and transportation routes

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Zulfa Hanan Ash’aari ◽  
Firuz Muhammad Ramli ◽  
Amir Hamzah Sharaai ◽  
Muhammad Nawaz Chaudhry ◽  
Samra Fatima
Keyword(s):  
Municipal Solid Waste ◽  
Solid Waste ◽  
Waste Collection ◽  
Solid Waste Collection ◽  
Transportation Routes

scholarly journals The Energy and Carbon Footprint of an Urban Waste Collection Fleet: A Case Study in Central Italy

Recycling ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 25
Author(s):  
Alessio Quintili ◽  
Beatrice Castellani
Keyword(s):  
Energy Consumption ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Co2 Emissions ◽  
Carbon Footprint ◽  
Local Level ◽  
Central Italy ◽  
Waste Collection ◽  
Solid Waste Collection

Municipal solid waste collection and transport are functional activities in waste management, with a significant energy and carbon footprint and a significant effect on the urban environment. An issue related to municipal solid waste collection and transport is their regional and municipal implementation, affected by sorting and recycling strategies at local level. An efficient collection is necessary to optimize the whole recycling process. The present paper shows the results of an energy, environmental, and economic evaluation of a case study, analyzing the fleet used for municipal solid waste collection and transport in 10 municipalities in Central Italy. The current scenario was compared with alternative scenarios on the basis of some parameters for performance evaluation: vehicles’ energy consumption, carbon footprint, routes, and costs. Results show that for passenger cars, the alternative scenario based on an entire fleet of dual compressed natural gas (CNG) vehicles led to a reduction of the CO2 emissions (−2675 kgCO2eq) in the analyzed period (January–August 2019) and a reduction of the energy consumption (−1.96 MJ km−1). An entire fleet of CNG vehicles led to an increase of CO2 emissions: +0.02 kgCO2eqkgwaste−1 (+110%) for compactors (35–75 q) and +0.09 kgCO2eqkgwaste−1 (+377%) for compactors (80–180 q). Moreover, both categories report a higher fuel consumption and specific energy consumption. For waste transport high-capacity vehicles, we propose the installation of a Stop-Start System, which leads to environmental and energy benefits (a saving of 38,332 kgCO2eq and 8.8 × 10−7 MJ km−1kgwaste−1). On three-wheeler vehicles, the installation of the Stop-Start System is completely disadvantageous.

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