scholarly journals A hybrid column generation approach for an industrial waste collection routing problem

2014 ◽  
Vol 71 ◽  
pp. 10-20 ◽  
Author(s):  
Kristian Hauge ◽  
Jesper Larsen ◽  
Richard Martin Lusby ◽  
Emil Krapper
MENDEL ◽  
2019 ◽  
Vol 25 (1) ◽  
pp. 15-22
Author(s):  
Vlastimír Nevrlý ◽  
Radovan Šomplák ◽  
Pavel Popela

Waste management is still an expanding eld which needs to be constantly enhanced so that waste transportation and treatment is as eective as possible. An important part of this process is a waste collection at the municipal level. Decision-making about daily routing for all vehicles from a heterogenous eet substantially in uences the expenses of technical services. The need of route scheduling comes also from the newly separated fractions. Transportation features include the capacity of vehicles, number and type of containers on the route, traffic light delays and many others. The mathematical model that properly describes the real practice of servicing containers has not been published yet. Moreover, routing problemsare generally not solvable by exact methods, so the appropriate heuristic algorithm has been developed. A case study with obtained results is discussed. This solution serves not only to improve the current operational situation, but also to create new route schedules for increasing number of collected commodities. 


2021 ◽  
Vol 12 (3) ◽  
pp. 122 ◽  
Author(s):  
Ricardo Ewert ◽  
Alexander Grahle ◽  
Kai Martins-Turner ◽  
Anne Magdalene Syré ◽  
Kai Nagel ◽  
...  

Electrification is a potential solution for transport decarbonization and already widely available for individual and public transport. However, the availability of electrified commercial vehicles like waste collection vehicles is still limited, despite their significant contribution to urban emissions. Moreover, there is a lack of clarity whether electric waste collection vehicles can persist in real world conditions and which system design is required. Therefore, we introduce a multi-agent-based simulation methodology to investigate the technical feasibility and evaluate environmental and economic sustainability of an electrified urban waste collection. We present a synthetic model for waste collection demand on a per-link basis, using open available data. The tour planning is solved by an open-source algorithm as a capacitated vehicle routing problem (CVRP). This generates plausible tours which handle the demand. The generated tours are simulated with an open-source transport simulation (MATSim) for both the diesel and the electric waste collection vehicles. To compare the life cycle costs, we analyze the data using total cost of ownership (TCO). Environmental impacts are evaluated based on a Well-to-Wheel approach. We present a comparison of the two propulsion types for the exemplary use case of Berlin. And we are able to generate a suitable planning to handle Berlin’s waste collection demand using battery electric vehicles only. The TCO calculation reveals that the electrification raises the total operator cost by 16–30%, depending on the scenario and the battery size with conservative assumptions. Furthermore, the greenhouse gas emissions (GHG) can be reduced by 60–99%, depending on the carbon footprint of electric power generation.


2017 ◽  
Vol 34 (03) ◽  
pp. 1740015 ◽  
Author(s):  
Chefi Triki

In many municipal waste collection systems, it is necessary to extend the planning horizon to more than one working day. This can happen, for example, in the collection of some recyclable articles. In this case, some of the streets must be served every day but others need only once every two days service. In this paper, we focus on planning the routing of the collection vehicles while extending the planning horizon to two working days. We propose a simple, but effective, heuristic approach and we carry out extensive computational experiments to evaluate its performance. We also apply our method to solve a real-case application related to the collection of recyclable wastes in a small Italian city.


Author(s):  
Amir Saeed Nikkhah Qamsari ◽  
Seyyed-Mahdi Hosseini-Motlagh ◽  
Seyed Farid Ghannadpour

2020 ◽  
Vol 10 (7) ◽  
pp. 2403
Author(s):  
Yanjun Shi ◽  
Lingling Lv ◽  
Fanyi Hu ◽  
Qiaomei Han

This paper addresses waste collection problems in which urban household and solid waste are brought from waste collection points to waste disposal plants. The collection of waste from the collection points herein is modeled as a multi-depot vehicle routing problem (MDVRP), aiming at minimizing the total transportation distance. In this study, we propose a heuristic solution method to address this problem. In this method, we firstly assign waste collection points to waste disposal plants according to the nearest distance, then each plant solves the single-vehicle routing problem (VRP) respectively, assigning customers to vehicles and planning the order in which customers are visited by vehicles. In the latter step, we propose the sector combination optimization (SCO) algorithm to generate multiple initial solutions, and then these initial solutions are improved using the merge-head and drop-tail (MHDT) strategy. After a certain number of iterations, the optimal solution in the last generation is reported. Computational experiments on benchmark instances showed that the initial solutions obtained by the sector combination optimization algorithm were more abundant and better than other iterative algorithms using only one solution for initialization, and the solutions with distance gap were obtained using the merge-head and drop-tail strategy in a lower CPU time compared to the Tabu search algorithm.


Author(s):  
Airam Expósito-Márquez ◽  
Christopher Expósito-Izquierdo ◽  
Julio Brito-Santana ◽  
José A. Moreno-Pérez

Author(s):  
Abdulwahab Almutairi

This paper addresses the real-life waste collection vehicle routing problem by applying Iterated Greedy (IG) and Randomized Iterated Greedy (RIG) in order to improve the processes. This kind of problem becomes more complex in developing countries in several aspects such as costs and fuel. Nowadays, the waste collection is considered as one of the interesting areas. There are three types of waste: commer-cial, residential and roll-on-roll-off. In this paper, we mainly consider the residential waste collection problem. The problem can be summa-rized as follows: a vehicle has to satisfy the demand at each customer location while satisfying the capacity of the vehicle for reducing the total cost. We report a case study that is related to waste collection in Riyadh, Kingdom of Saudi Arabia. To solve the case study problem, IG and RIG were employed. Experiments have been done on the case study data and show a better performance when compared IG algo-rithm results with RIG algorithm results.  


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