Metaheuristics for the waste collection vehicle routing problem with time windows

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis there is a set of waste disposal facilities, a set of customers at which waste is collected and an unlimited number of homogeneous vehicles based at a single depot. Empty vehicles leave the depot and collect waste from customers, emptying themselves at the waste disposal facilities as and when necessary. Vehicles return to the depot empty. We take into consideration time windows associated with customers, disposal facilities and the depot. We also have a driver rest period. The problem is solved heuristically. A neighbour set is defined for each customer as the set of customers that are close, but with compatible time windows. This thesis uses six different procedures to obtain initial solutions for the problem. Then, the initial solutions from these procedures are improved in terms of the distance travelled using our phase 1 and phase 2 procedures, whereas we reduce the number of vehicles used using our vehicle reduction (VR) procedure. In a further attempt to improve the solutions three metaheuristic algorithms are presented, namely tabu search (TS), variable neighbourhood search (VNS) and variable neighbourhood tabu search (VNTS). Moreover, we present a modified disposal facility positioning (DFP), reverse order and change tracking procedures. Using all these procedures presented in the thesis, four solution procedures are reported for the two benchmark problem sets, namely waste collection vehicle routing problems with time windows (VRPTW) and multi-depot vehicle routing problem with inter-depot routes (MDVRPI). Our solutions for the waste collection VRPTW problems are compared with the solutions from Kim et al (2006), and our solutions for the MDVRPI problems are compared with Crevier et al (2007). Computational results for the waste collection VRPTW problems indicate that our algorithms produce better quality solutions than Kim et al (2006) in terms of both distance travelled and number of vehicles used. However for the MDVRPI problems, solutions from Crevier et al (2007) outperform our solutions.Ministry of Higher Education, Malaysi

Housing Criteria/Location Selection Using Analytic Hierarchy Process : A Universiti Utara Malaysia Study

The report presents the findings of a survey of the housing location selection preferences among the Malaysian house buyers, in particular the Universiti Utara Malaysia (UUM) staff. In this study, eight criteria for housing location selection decision were determined and five housing locations were identified. The decision problem was structured into a three level hierarchy using Analytic Hierarchy Process (AHP) technique. The findings revealed that the most important criteria considered by UUM staff in selecting their housing location was road facilities, followed by religious centres and cost of living. Three factors namely, gender, marital status and incomes that might affect one's decision when selecting a housing location were also discussed in this study. Generally, those who were married with family consider road facilities as the most important criteria whereas bachelor house buyers tend to give priority to cost of living. This criterion was also the most important for the first incomes group (RM5000 or less) while social standing of an area was the top criteria for the second incomes group (above RM5000). However, the gender factor did not give much influence for the UUM staff in selecting their housing location. Both the male and female staff considered road facilities the most important criteria. The results of this study may be useful to housing - developers because it provides information regarding the importance of location selection criteria and thus may help housing developers to choose the best housing location to match the house buyers' needs. The AHP model also offers house buyers a systematic framework for making a multiple criteria decision that involves huge investment such as buying a house

Metaheuristics for the waste collection vehicle routing problem with time windows, driver rest period and multiple disposal facilities

In this problem there is a set of waste disposal facilities, a set of customers at which waste is collected and an unlimited number of homogeneous vehicles based at a single depot.Empty vehicles leave the depot and collect waste from customers, emptying themselves at the waste disposal facilities as and when necessary.Vehicles return to the depot empty.We take into consideration time windows associated with customers, disposal facilities and the depot. We also have a driver rest period.The problem is solved heuristically.A neighbour set is defined for each customer as the set of customers that are close, but with compatible time windows. A procedure that attempts to fully utilise a vehicle is used to obtain an initial solution, with this initial solution being improved using an interchange procedure.We present two metaheuristic algorithms using tabu search and variable neighbourhood search that are based around the neighbour sets.We also present a metaheuristic based on variable neighbourhood tabu search, where the variable neighbourhood is searched via tabu search.Computational results are presented for publicly available waste collection problems involving up to 2092 customers and 19 waste disposal facilities, which indicate that our algorithms produce better quality solutions than previous work presented in the literature

Metaheuristics for the waste collection vehicle routing problem with time windows

In this thesis there is a set of waste disposal facilities, a set of customers at which waste is collected and an unlimited number of homogeneous vehicles based at a single depot. Empty vehicles leave the depot and collect waste from customers, emptying themselves at the waste disposal facilities as and when necessary. Vehicles return to the depot empty. We take into consideration time windows associated with customers, disposal facilities and the depot. We also have a driver rest period. The problem is solved heuristically. A neighbour set is defined for each customer as the set of customers that are close, but with compatible time windows. This thesis uses six different procedures to obtain initial solutions for the problem. Then, the initial solutions from these procedures are improved in terms of the distance travelled using our phase 1 and phase 2 procedures, whereas we reduce the number of vehicles used using our vehicle reduction (VR) procedure. In a further attempt to improve the solutions three metaheuristic algorithms are presented, namely tabu search (TS), variable neighbourhood search (VNS) and variable neighbourhood tabu search (VNTS). Moreover, we present a modified disposal facility positioning (DFP), reverse order and change tracking procedures. Using all these procedures presented in the thesis, four solution procedures are reported for the two benchmark problem sets, namely waste collection vehicle routing problems with time windows (VRPTW) and multi-depot vehicle routing problem with inter-depot routes (MDVRPI). Our solutions for the waste collection VRPTW problems are compared with the solutions from Kim et al (2006), and our solutions for the MDVRPI problems are compared with Crevier et al (2007). Computational results for the waste collection VRPTW problems indicate that our algorithms produce better quality solutions than Kim et al (2006) in terms of both distance travelled and number of vehicles used. However for the MDVRPI problems, solutions from Crevier et al (2007) outperform our solutions.EThOS - Electronic Theses Online ServiceMinistry of Higher Education, MalaysiaGBUnited Kingdo

Optimization capacity planning problem on conference scheduling

Designing a conference scheduling involves various factors that need to be considered in order to fulfill the participants' preferences.Capacity planning problem is a main focus in this study in order to assign the papers that are to be presented into time slots based on paper of interest.All the presentation papers are assigned efficiently to avoid too many participants in a particular session.Goal Programming model has been developed to produce a schedule that maximizes the participants' satisfaction in terms of capacity planning subject to the capacity constraints.The proposed schedule shows that almost 93% of the time slots are fully utilized and fulfill the capacity constraint. Moreover, it could help the conference committee to better understand the preferences of participant prior to construct the schedule in future

Economic tour package model using heuristic

A tour-package is a prearranged tour that includes products and services such as food, activities, accommodation, and transportation, which are sold at a single price.Since the competitiveness within tourism industry is very high, many of the tour agents try to provide attractive tour-packages in order to meet tourist satisfaction as much as possible.Some of the criteria that are considered by the tourist are the number of places to be visited and the cost of the tour-packages.Previous studies indicate that tourists tend to choose economical tour-packages and aiming to visit as many places as they can cover. Thus, this study proposed tour-package model using heuristic approach.The aim is to find economical tour-packages and at the same time to propose as many places as possible to be visited by tourist in a given geographical area particularly in Langkawi Island.The proposed model considers only one starting point where the tour starts and ends at an identified hotel.This study covers 31 most attractive places in Langkawi Island from various categories of tourist attractions. Besides, the allocation of period for lunch and dinner are included in the proposed itineraries where it covers 11 popular restaurants around Langkawi Island. In developing the itinerary, the proposed heuristic approach considers time window for each site (hotel/restaurant/place) so that it represents real world implementation. We present three itineraries with different time constraints (1-day, 2-day and 3-day tour-package).The aim of economic model is to minimize the tour-package cost as much as possible by considering entrance fee of each visited place.We compare the proposed model with our uneconomic model from our previous study. The uneconomic model has no limitation to the cost with the aim to maximize the number of places to be visited.Comparison between the uneconomic and economic itinerary has shown that the proposed model have successfully achieved the objective that minimize the tour cost and cover maximum number of places to be visited

Efficiency of heuristic algorithms in solving waste collection vehicle routing problem: a case study

This paper investigated the efficiency of six heuristic algorithms from prior studies in the attempt to solve issues related to waste collection, namely: (i) Nearest Greedy (NG), (ii) Further from Depot (FFD), (iii) Different Initial Customer (DIC), (iv) Savings Approach, (v) Sweep Algorithm, and (vi) Different Initial Customer based on Sweep Algorithm. In fact, these heuristics have been employed to solve several routing problems in past studies, but the performance of each heuristic has never been compared. Hence, this paper looked into the efficiency of these heuristics by testing them on a real case study of waste collection problem in a district located at the north of Peninsular Malaysia. Several solutions obtained from these heuristics were compared with solutions implemented by the waste collection company, especially in terms of the total distance travelled. As a result, the computational results exhibited that DIC generated the best solutions, when compared to other heuristics, with a 12% reduction of the total travel distance

Waste collection vehicle routing problem benchmark datasets and case studies: A review

Waste collection vehicle routing problem (WCVRP) is one of the most studied areas and has received high interest from the modern society today.This corresponds to the cost efficiency, population growth, and environmental concerns.The growth of the WCVRP awareness is the result of continuous supports from government and private organizations.This paper reviews severa established benchmark datasets and successful real-life case studies. Respectively billions of dollars have been saved from the operational costs.The current trend for benchmark datasets presented and case studies are accordingly grouped by countries and continents, thus revealing the need for WCVRP. Investigation on objectives, constraints and algorithms are also discussed. Results showed the increased interest of researchers in using benchmark datasets as well as the case studies and some of the constraints that should be considered in WCVRP.It also suggested that environmental or quality of service issues can be integrated into the common objectives of minimizing cost and distance travelled.Methods used in WCVRP are exact methods and approximate methods.Results showed that approximate methods have the capability in providing good results for large-scale data. Conclusively, this study analyzes the gap and provides recommendations for researches

Resource planning for a single landfill site selection model based on greedy strategy: a case study

Landfilling, which has emerged as the most common method for disposal of solid waste and selection of appropriate landfill for solid waste management, is a crucial aspect in urban planning. It is compulsory to consider the various criteria, such as environmental, economic, and social criteria, in order to get the best search outcomes that can minimise the adverse effects of the surrounding population. As widely known, the process of selecting new landfills is divided into two important phases, which are: 1) the determination of potential candidate locations through an initial screening, and 2) suitability assessment based on several criteria. Previously, issues related to landfill site selection have been successfully solved by using Geographic Information System (GIS) and Multiple Criteria Decision-Making (MCDM) techniques, either individually or as an integrated approach. With that, this research aims to assist the authorities in planning a single landfill site selection by utilising all the available resources, which translates being cost-effective. Therefore, the Nearest Greedy (NG) technique had been employed to assess all five potential candidate locations by considering several related constraints. Next, the solutions were ranked based on the total distance travelled by vehicles in completing the overall waste collection process. The proposed approach was tested on a real dataset of the waste collection problem in a district located within the Northern Region of Peninsular Malaysia, which consisted of 146 residential areas and involving up to 18749 unit premises. After that, the solution obtained was compared with the present operating landfill facility, in which Candidate 4 appeared as the best alternative with a 6.74% reduction of total distance travelled, in comparison to the present operating landfill method. As such, the proposed solution may aid the local authorities and serve as a guideline in identifying suitable locations for waste disposal based on availability resources, which can discard unnecessary expenditure, such as fuel consumption

Penyeimbangan beban kerja di kalangan pemandu lori tangki: Satu kajian kes

Kajian ini membincangkan masalah beban keja seimbang bagi pemandu lori tangki disebuah syarikat pengangkutan yang berpangkalan di Pelabuhan Kelang. Bagi menyeimbangkan jumlah muatan yang perlu dibawa oleh setiap pemandu agar beban kerja adalah sama, satu model pengaturcaraan integer telah dibangunkan dengan mengambilkira beberapa kekangan yang telah dikenal pasti. Antara kekangan tersebut ialah jumlah trip yang dibawa setiap pemandu tidak boleh melebihi jumlah hari bekeja dalam sebulan. Model ini dibangunkan bertujuan menyeimbangkan beban keja dengan memfokuskan kepada jumlah kapasiti yang dibawa bagi setiap pekerja supaya setiap pekerja akan membawa jumlah kapasiti yang seimbang. Model tersebut diselesaikan dengan menggunkan perisian LOG. Kajian ini juga turut memuatkan analisis sensitiviti (what - if scenario) bagi melihat berapakah jumlah pekerja sebenar yang diperlukan bagi mengangkut muatan tersebut. Hasilnya, setiap pemandu lori akan membawa antara 354 - 408 tan setiap bulan dengan bilangan trip setiap pekerja sebanyak 11 - 13 trip. Dapatan kajian ini berguna kepada pihak pengurusan syarikat dalam mnjanakan pengagihan tugasan bulanan yang lebih berkesan