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Designing optimal subsidy schemes and recycling plans for sustainable treatment of construction and demolition waste

Lei Yu, Qian Ge, Ke Han, Wen Ji, Yueqi Liu

Abstract

More than 10 billion tons of construction and demolition waste (CW) are generated globally each year, exerting a significant impact on the environment. In the CW recycling process, the government and the carrier are the two primary stakeholders. The carrier is responsible for transporting CW from production sites to backfill sites or processing facilities, with a primary focus on transport efficiency and revenue. Meanwhile, the government aims to minimize pollution from the recycling system, which is influenced by transport modes, shipment distances, and the processing methods used for CW. This paper develops a bi-objective, bi-level optimization model to address these challenges. The upper-level model is a linear programming model that optimizes the government's subsidy scheme, while the lower-level model is a minimum-cost flow model that optimizes the carrier's recycling plan. A hybrid heuristic solution method is proposed to tackle the problem's complexity. A case study in Chengdu, China, demonstrates the computational efficiency of the model and its small solution gap. With an optimized subsidy scheme and recycling plan, pollution can be reduced by over 29.29% through a relatively small investment in subsidies.

Designing optimal subsidy schemes and recycling plans for sustainable treatment of construction and demolition waste

Abstract

More than 10 billion tons of construction and demolition waste (CW) are generated globally each year, exerting a significant impact on the environment. In the CW recycling process, the government and the carrier are the two primary stakeholders. The carrier is responsible for transporting CW from production sites to backfill sites or processing facilities, with a primary focus on transport efficiency and revenue. Meanwhile, the government aims to minimize pollution from the recycling system, which is influenced by transport modes, shipment distances, and the processing methods used for CW. This paper develops a bi-objective, bi-level optimization model to address these challenges. The upper-level model is a linear programming model that optimizes the government's subsidy scheme, while the lower-level model is a minimum-cost flow model that optimizes the carrier's recycling plan. A hybrid heuristic solution method is proposed to tackle the problem's complexity. A case study in Chengdu, China, demonstrates the computational efficiency of the model and its small solution gap. With an optimized subsidy scheme and recycling plan, pollution can be reduced by over 29.29% through a relatively small investment in subsidies.

Paper Structure

This paper contains 30 sections, 2 theorems, 20 equations, 9 figures, 4 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Literature review
  3. CW management scheme
  4. Economic leverage for CW management scheme
  5. Mathematical formulations
  6. Problem statement
  7. The strategy of the carrier
  8. The strategy of the government
  9. Calculate method of pollution
  10. Mathematical formulation
  11. Solution approach
  12. Solution algorithm
  13. Global framework
  14. Upper-level search based on MOPSO
  15. Accelerated lower-level problem solving
  16. ...and 15 more sections

Key Result

Proposition 1

$F_1(\mathbf{x}_{M1}^*)$ is the upper bound of the pollution index $F_1$ in model [M3].

Figures (9)

  • Figure 1: The structure of bi-level model.
  • Figure 2: Time-space network $\mathcal{G}$.
  • Figure 3: Frequency distribution of trucks held by carriers
  • Figure 4: The location of sites.
  • Figure 5: The variations of model gap with run time. Ten repetitions of the experiment for model [M1].
  • ...and 4 more figures

Theorems & Definitions (7)

  • Definition 1: Fully loaded arc
  • Definition 2: Deadheading arc
  • Definition 3: Service arc
  • Proposition 1
  • proof
  • Proposition 2
  • proof