Extended Maximal Covering Location and Vehicle Routing Problems in Designing Smartphone Waste Collection Channels: A Case Study of Yogyakarta Province, Indonesia

Sari, Diana Puspita; Masruroh, Nur Aini; Asih, Anna Maria Sri

doi:10.3390/su13168896

Cited by 10 publications

(7 citation statements)

References 64 publications

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“…The nearest neighbor algorithm is chosen because it has been used in several VRP studies and it is proven lightweight in the computation process [29]- [31]. Due to its simplicity, nearest neighbor algorithm was combined with other algorithms, such as Tabu search [32]. Moreover, as a heuristic method, the nearest neighbor is proven better than other heuristic methods [33], more realistic in solving real world problem [34], and widely used in many travelling salesman problem applications [35].…”

Section: Methodsmentioning

confidence: 99%

Pickup and delivery problem in the collaborative city courier service by using genetic algorithm and nearest distance

Kusuma

Kallista

2022

Bulletin EEI

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One problem in collaborative pickup delivery problem (PDP) was excessive outsourced jobs. It happened in many studies on the collaborative PDP. Besides, the revenue sharing in it was unclear although important. This work aimed to propose a novel collaborative PDP model which minimizes total travel distance while maintains low outsourced jobs. It proposed several contributions. First, it prioritized internal jobs first rather than full collaborative model. Second, it proposed new revenue sharing model. It adopted cluster-first route-second and mixed pickup and delivery. It was developed by combining the genetic algorithm and nearest distance algorithm where the genetic algorithm was used in the clustering process and the nearest distance was used in the routing process. The simulation result shows that the proposed model was better than the comparing models: (1) combined K-means and genetic algorithm model (KMGA) and (2) combined simulated annealing and last-in first-out (SNLIFO) model. When the number of orders was high (300 units), the total travel distance of the proposed model was 37 percent lower than the KMGA model and 30 percent lower than the SNLIFO model. In average, the outsourcing rate of the proposed model was 70 percent lower than the previous models.

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Section: Methodsmentioning

confidence: 99%

Pickup and delivery problem in the collaborative city courier service by using genetic algorithm and nearest distance

Kusuma

Kallista

2022

Bulletin EEI

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“…Based on the calculation results for determining the primary collection center (Sari, Masruroh & Asih, 2021d), as many as 30 PCCs must be built. This facility serves as a collection center to provide convenience to consumers.…”

Section: Primary Collection Center (Pcc)mentioning

confidence: 99%

Economic and environmental benefits of e-waste management networks design in Yogyakarta province, Indonesia

Sari,

Masruroh,

Asih

2024

JIEM

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Purpose: Electronic devices consumption, especially smartphones for communication, have increased significantly, causing the potential for electronic waste to increase too. However, the high potential of this flow has not been matched by good waste management. This study aims to develop a management network for e-waste that collaborates formal and informal channels to provide optimal supply chain benefits in terms of economic and environmental aspectsDesign/methodology/approach: This research designs an e-waste management network followed by building a single-objective mathematical model that considers economic and environmental aspects. This model was solved using Mixed Integer Linear Programming.Findings: The supply chain will benefit from the proposed management network by collaborating formal and informal channels. With an incentive of 10,000 IDR, it is hoped that it will be able to invite consumers and informal collectors to collect waste informal channels. The total profit from managing electronic waste supply every month from Yogyakarta Province is 5.529 x 1010 IDR with the composition, consumers 81.2%, informal 13.3% channel obtained from informal collectors and repairing centers and 2.1% for formal channels, and there is an intangible profit of 3.4%. The formal channel provides more significant benefits than the informal, but requires a significant investment. This formal channel feasible if at least 33% of the total supply goes to this channel.Research limitations/implications: The model designed is deterministic. Therefore, it can be developed into a probabilistic model for further research to represent more real cases in the field.Practical implications: Regulation is the factor that most influences consumers' intentions and behavior to participate in e-waste management programs. It will be able to change consumer behavior by forcing consumers to participate in e-waste collection programs. Therefore, a government regulation is needed that organizes and supervises the implementation of the proposed management model.Social implications: Currently, the practice developing in the community is that the informal sector carries out smartphone waste management, therefore in the designs made, informal actors are still given space in waste management for the repair process and the secondhand market. Meanwhile, further processing, such as recycling, must be carried out through formal channels taking into account the environmental impact.Originality/value: Few studies have developed an electronic waste management model by collaborating informal and formal channels that consider economic and environmental aspects, and its implementation is organized and supervised by government regulations.

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“…In other regions in Indonesia, there is no known information on e-waste collection facilities sourced from households that are well managed by local governments. For example, in Yogyakarta Province, there was no e-waste collection facility [25]. Although there are many studies on e-waste management, very few still discuss the latest data, classification, collection mechanisms, and the flow of e-waste information sourced from households in Jakarta, Indonesia.…”

Section: Introductionmentioning

confidence: 99%

Current status of household e-waste management in Jakarta, Indonesia

Soesanto

Maarif

Anwar

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Managing electronic waste or e-waste in Jakarta Province, Indonesia, is essential to support sustainable development goals (SDGs). E-waste contains toxic materials and is harmful to the environment while having the potential for a circular economy if appropriately managed. This study aims to analyze electronic waste management, formally originating from households in Jakarta Province, from the aspects of the e-waste collection mechanism, the type of e-waste, the amount of e-waste, and the flow of e-waste information using a descriptive method. The research findings are that the Jakarta Regional Government collects e-waste through three mechanisms: e-waste direct pickup (35.5%), e-waste drop box (0.6%), and e-waste temporary garbage collection (63.9%). The total amount of e-waste managed formally was 33,289 kg in 2021. In practice, there are five types of e-waste: television, lights, batteries, printer cartridges, and other e-waste. The effectiveness of the e-waste collection process needs improving. The amount of e-waste collected can be increased. One of the robust recommendations for improving e-waste management in Jakarta is integrating innovative digital platform-based technology and multi-actor collaboration. This research supports preliminary data and information on the circular economy’s potential and the formulation of specific regulations on e-waste in Indonesia.

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Extended Maximal Covering Location and Vehicle Routing Problems in Designing Smartphone Waste Collection Channels: A Case Study of Yogyakarta Province, Indonesia

Cited by 10 publications

References 64 publications

Pickup and delivery problem in the collaborative city courier service by using genetic algorithm and nearest distance

Pickup and delivery problem in the collaborative city courier service by using genetic algorithm and nearest distance

Economic and environmental benefits of e-waste management networks design in Yogyakarta province, Indonesia

Current status of household e-waste management in Jakarta, Indonesia

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