Solving an Urban Waste Collection Problem Using Ants Heuristics

This paper describes the methodology that we have applied for the solution of an urban waste collection problem in the municipality of Sant Boi de Llobregat, within the metropolitan area of Barcelona (Spain). The basic nature of the considered problem is that of a capacitated arc routing problem, although it has several specific characteristics, mainly derived from trafic regulations. We present the model that we have built for the problem, which results after an appropriate transformation of the problem into a node routing one. We also present the ant colonies heuristics that we have used to obtain the solutions to the problem. These combine constructive methods, based on nearest neighbor and on nearest insertion, with a local search that explores various neighborhoods. The application of the proposed methods gives results that improve considerably the ones that were previously used in the municipality.Peer Reviewe

Waste Collection Vehicle Routing Problem: Literature Review

Waste generation is an issue which has caused wide public concern in modern societies, not only for the quantitative rise of the amount of waste generated, but also for the increasing complexity of some products and components. Waste collection is a highly relevant activity in the reverse logistics system and how to collect waste in an efficient way is an area that needs to be improved. This paper analyzes the major contribution about Waste Collection Vehicle Routing Problem (WCVRP) in literature. Based on a classification of waste collection (residential, commercial and industrial), firstly the key findings for these three types of waste collection are presented. Therefore, according to the model (Node Routing Problems and Arc Routing problems) used to represent WCVRP, different methods and techniques are analyzed in this paper to solve WCVRP. This paper attempts to serve as a roadmap of research literature produced in the field of WCVRP

Facility Location Problems: Models, Techniques, and Applications in Waste Management

This paper presents a brief description of some existing models of facility location problems (FLPs) in solid waste management. The study provides salient information on commonly used distance functions in location models along with their corresponding mathematical formulation. Some of the optimization techniques that have been applied to location problems are also presented along with an appropriate pseudocode algorithm for their implementation. Concerning the models and solution techniques, the survey concludes by summarizing some recent studies on the applications of FLPs to waste collection and disposal. It is expected that this paper will contribute in no small measure to an integrated solid waste management system with specific emphasis on issues associated with waste collection, thereby boosting the drive for e�ective and e�cient waste collection systems. The content will also provide early career researchers with some necessary starting information required to formulate and solve problems relating to FLP

Some aspects of the approach to modelling assignments of the means for the tasks in municipal services companies

In this article the assignment problem of vehicles to tasks in municipal services companies in the context of designating the minimum routes of vehicles was presented. The mathematical model of the assignment problem was developed, and proposed a method for solving the assignment problem in municipal services companies. The method consists of two stages i.e. the stage of designating the minimum route consisting of all tasks and the stage of designating individual routes for each vehicle. In the light of considerations indicating individual routes we designate the tasks to the implementation, which is the equivalent of solving the assignment problem. The genetic algorithm for solving the optimization problem presented in the first stage of the method was proposed. Verification of this algorithm confirmed its effectiveness.W artykule przedstawiono zagadnienie przydziału pojazdów do zadań w przedsiębiorstwach komunalnych w kontekście wyznaczania minimalnych tras jazdy pojazdów. Opracowano model matematyczny zagadnienia przydziału oraz zaproponowano metodę rozwiązującą zagadnienie przydziału w przedsiębiorstwach komunalnych. Metoda składa się z dwóch etapów, tj. etapu wyznaczającego minimalną trasę składającą się ze wszystkich zadań oraz etapu wyznaczania tras indywidualnych dla poszczególnych pojazdów. W świetle przeprowadzonych rozważań wskazując trasy indywidualne wyznaczymy zadania do realizacji, co jest tożsame z rozwiązaniem problemu przydzia- łu. Zaproponowano algorytm genetyczny do rozwiązania problemu optymalizacyjnego przedstawionego w pierwszym etapie metody. Weryfikacja algorytmu potwierdziła jego skuteczność

Optimization of municipal solid waste collection routes based on the containers' fill status data

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201

Solid Waste Collection Optimization: A literature Review

The urban population saw an increase of 80 million in 2019. The accelerated movement of people towards urban centres along with annual increasing per capita waste generation calls for an urgent need to address the rising solid waste generation. Contemporary pandemic of Covid-19 puts the demand all time high for revival and optimizing solid waste management system. For optimizing solid waste management, solid waste collection is the most important aspect of process as it includes majority of financial inputs. This article aims to provide literature review regarding different methodologies and criteria for solid waste collection optimization. The article also examines trends and areas of future research along with unexplored and budding domains. This would help reader identifying his interest area besides getting a comprehensive understanding of research trends. The study could also be used by waste management firms to analyze, compare different methods, their performance and their suitability under different environment conditions.

OPTIMAL ROUTE DETERMINATION FOR POSTAL DELIVERY USING ANT COLONY OPTIMIZATION ALGORITHM

There are a lot of optimization challenges in the world, as we all know. The vehicle routing problem is one of the more complex and high-level problems. Vehicle Routing Problem is a real-life problem in the Postal Delivery System logistics and, if not properly attended to, can lead to wastage of resources that could have been directed towards other things. Several studies have been carried out to tackle this problem using different techniques and algorithms. This study used the Ant Colony Optimization Algorithm along with some powerful APIs to find an optimal route for the delivery of posts to customers in a Postal Delivering System. When Ant Colony Optimization Algorithm is used to solve the vehicle routing problem in transportation systems, each Ant's journey is mere “part” of a feasible solution. To put it in another way, numerous ants' pathways might make up a viable solution. Routes are determined for a delivery vehicle, with the objective of minimizing customer waiting time and operation cost. Experimental results indicate that the solution is optimal and more accurat

Inventory routing for dynamic waste collection

We consider the problem of collecting waste from sensor equipped underground containers. These sensors enable the use of a dynamic collection policy. The problem, which is known as a reverse inventory routing problem, involves decisions regarding routing and container selection. In more dense networks, the latter becomes more important. To cope with uncertainty in deposit volumes and with fluctuations due to daily and seasonal e ects, we need an anticipatory policy that balances the workload over time. We propose a relatively simple heuristic consisting of several tunable parameters depending on the day of the week. We tune the parameters of this policy using optimal learning techniques combined with simulation. We illustrate our approach using a real life problem instance of a waste collection company, located in The Netherlands, and perform experiments on several other instances. For our case study, we show that costs savings up to 40% are possible by optimizing the parameters

Optimization of vehicle routing and scheduling with travel time variability - application in winter road maintenance

This study developed a mathematical model for optimizing vehicle routing and scheduling, which can be used to collect travel time information, and also to perform winter road maintenance operations (e.g., salting, plowing). The objective of this research was to minimize the total vehicle travel time to complete a given set of service tasks, subject to resource constraints (e.g., truck capacity, fleet size) and operational constraints (e.g., service time windows, service time limit). The nature of the problem is to design vehicle routes and schedules to perform the required service on predetermined road segments, which can be interpreted as an arc routing problem (ARP). By using a network transformation technique, an ARP can be transformed into a well-studied node routing problem (NRP). A set-partitioning (SP) approach was introduced to formulate the problem into an integer programming problem (I PP). To solve this problem, firstly, a number of feasible routes were generated, subject to resources and operational constraints. A genetic algorithm based heuristic was developed to improve the efficiency of generating feasible routes. Secondly, the corresponding travel time of each route was computed. Finally, the feasible routes were entered into the linear programming solver (CPL EX) to obtain final optimized results. The impact of travel time variability on vehicle routing and scheduling for transportation planning was also considered in this study. Usually in the concern of vehicle and pedestrian\u27s safety, federal, state governments and local agencies are more leaning towards using a conservative approach with constant travel time for the planning of winter roadway maintenance than an aggressive approach, which means that they would rather have a redundancy of plow trucks than a shortage. The proposed model and solution algorithm were validated with an empirical case study of 41 snow sections in the northwest area of New Jersey. Comprehensive analysis based on a deterministic travel time setting and a time-dependent travel time setting were both performed. The results show that a model that includes time dependent travel time produces better results than travel time being underestimated and being overestimated in transportation planning. In addition, a scenario-based analysis suggests that the current NJDOT operation based on given snow sector design, service routes and fleet size can be improved by the proposed model that considers time dependent travel time and the geometry of the road network to optimize vehicle routing and scheduling. In general, the benefit of better routing and scheduling design for snow plowing could be reflected in smaller minimum required fleet size and shorter total vehicle travel time. The depot location and number of service routes also have an impact on the final optimized results. This suggests that managers should consider the depot location, vehicle fleet sizing and the routing design problem simultaneously at the planning stage to minimize the total cost for snow plowing operations

Solving a capacitated waste collection problem using an open-source tool

Increasing complexity in municipal solid waste streams worldwide is pressing Solid Waste Management Systems (SWMS), which need solutions to manage the waste properly. Waste collection and transport is the first task, traditionally carried out by countries/municipalities responsible for waste management. In this approach, drivers are responsible for decision-making regarding collection routes, leading to inefficient resource expenses. In this sense, strategies to optimize waste collection routes are receiving increasing interest from authorities, companies and the scientific community. Works in this strand usually focus on waste collection route optimization in big cities, but small towns could also benefit from technological development to improve their SWMS. Waste collection is related to combinatorial optimization that can be modeled as the capacitated vehicle routing problem. In this paper, a Capacitated Waste Collection Problem will be considered to evaluate the performance of metaheuristic approaches in waste collection optimization in the city of Bragança, Portugal. The algorithms used are available on Google OR-tools, an open-source tool with modules for solving routing problems. The Guided Local Search obtained the best results in optimizing waste collection planning. Furthermore, a comparison with real waste collection data showed that the results obtained with the application of OR-Tools are promising to save resources in waste collection.This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R &D Units Project Scope: UIDB/05757/2020, UIDB/00690/2020, UIDB/50020/2020, and UIDB/00319/2020. Adriano Silva was supported by FCT-MIT Portugal PhD grant SFRH/BD/151346/2021, and Filipe Alves was supported by FCT PhD grant SFRH/BD/143745/2019