Facility location and scale optimisation in closed-loop supply chain

Zhen, Lu; Sun, Qiuji; Wang, Kai; Zhang, Xiaotian

doi:10.1080/00207543.2019.1587189

Cited by 28 publications

(7 citation statements)

References 46 publications

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“…Gambella et al ( 2019 ) presented a multi-period model with realistic constraints for waste treatment facilities. Another two-stage stochastic model was introduced by Zhen et al ( 2019 ), who dealt with a closed-loop supply chain and its operational costs under uncertain demands and returns. Scenario-based models are not exceptional nowadays: for example, a two-stage model was applied to an internal waste resource system by An et al ( 2016 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal location and operation of waste-to-energy plants when future waste composition is uncertain

et al. 2022

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In many countries, waste management is increasingly geared towards a circular economy, aiming for a sustainable society with less waste generation, fewer landfills, and a higher rate of recycling. Waste-to-Energy (WtE) plants, which convert waste into heat and energy, can contribute to the circular economy by utilizing types of waste that cannot be recycled. Due to the varying quality of sorting and socio-economic conditions in individual regions, the waste composition differs between regions and has an uncertain future development. Waste composition significantly affects the operation of WtE plants due to differences in energy potential. This paper supports strategic capacity planning for waste energy recovery by introducing a two-stage stochastic mixed-integer linear programming model that captures waste composition uncertainty through scenarios of possible future development. The results of the model provide insights into the economics of operation and identify important factors in the sustainability of the waste handling system. The model is demonstrated on an instance with six scenarios for waste management in the Czech Republic for the year 2030. The solution of the proposed model is to build 14 new WtE plants with a total capacity of 1970 kt in addition to the four existing plants with a capacity of 831 kt. The annual energy recovery capacity is expected to increase almost four times to satisfy EU directives that restrict waste landfilling.

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Section: Literature Reviewmentioning

confidence: 99%

Optimal location and operation of waste-to-energy plants when future waste composition is uncertain

et al. 2022

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“…In addition, the relationship between the location of logistics facilities and vehicle travel distances for shipments associated with the facilities has also been analyzed [52]. Some other conventional approaches to location include heuristics [53], MIP models [54] dynamic programming [55], nonlinear programming [56,57], quadratic programming [58,59], hierarchical analysis process (AHP) [60], and artificial intelligence (AI) techniques [61], such as specialist systems, artificial neural networks (ANNs), metaheuristics or fuzzy set theory [62]. In the recent works, the trend is to consider a large part of the logistics distribution network incorporating the other vertices of the logistics triangle (transport and inventory), to propose increasingly compensatory solutions.…”

Section: Related Literaturementioning

confidence: 99%

Location of Urban Logistics Spaces (ULS) for Two-Echelon Distribution Systems

Ruiz-Meza

Meza-Peralta

Montoya‐Torres

et al. 2021

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The main concern in city logistics is the need to optimize the movement of goods in urban contexts, and to minimize the multiple costs inherent in logistics operations. Inspired by an application in a medium-sized city in Latin America, this paper develops a bi-objective mixed linear integer programming (MILP) model to locate different types of urban logistics spaces (ULS) for the configuration of a two-echelon urban distribution system. The objective functions seek to minimize the costs associated with distance traveled and relocation, in addition to the costs of violation of time windows. This model considers heterogeneous transport, speed assignment, and time windows. For experimental evaluation, two operational scenarios are considered, and Pareto frontiers are obtained to identify the efficient non-dominated solutions to select the most feasible ones from such a set. A case study of a distribution company of goods for supermarkets in the city of Barranquilla, Colombia, is also used to validate the proposed model. These solutions allow decision-makers to define the configuration of ULS networks for urban product delivery.

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“…They have addressed the crucial issues of cross-border trade. Similarly, Liao (2018) proposed a mixed-integer nonlinear model for reverse logistics and solved it using a hybrid GA. Zhen et al (2019) proposed a two-stage stochastic MINLP model for facility location in a closedloop supply chain and solved it using an improved tabu search approach. In a seminal work, Reddy et al (2018) used three-phase heuristics to solve the model.…”

Section: Review Of Closed-loop Supply Chains and Reverse Logisticsmentioning

confidence: 99%

Designing dynamic reverse logistics network for post-sale service

Mishra

Singh

2020

Ann Oper Res

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The paper addresses the problem of designing a multi-country production-distribution network that also provides services such as repairs and remanufacturing. The proposed work concentrates primarily on post-sale service provided by the firm under warranty returns. The proposed model assumes that existing warehouses can also serve as collection centres or repair centres for reverse logistics. In addition, the model also explores the possibility of establishing a new facility. Hybrid facilities are considered because of their huge cost-cutting potential due to equipment sharing and space sharing. The capacity of hybrid facilities can be expanded to a predefined limit to process returned products without hampering forward logistics operations. However, if a product cannot be repaired at the warehouse, it is transported to the plant for remanufacturing. The model optimizes the overall configuration and operation cost of the production-distribution network. The production-distribution model developed in the paper is a mixed-integer nonlinear program (MINLP) that is later transformed to a mixed-integer linear program to reduce the solution time. The usefulness of the model is illustrated using a randomly generated dataset. The model identifies (a) the optimal locations/allocations of the existing/new facilities, (b) the distribution of returned products for refurbishing and remanufacturing, and (c) the capacity expansion of the existing plants and warehouses to facilitate remanufacturing and repair services.

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Facility location and scale optimisation in closed-loop supply chain

Cited by 28 publications

References 46 publications

Optimal location and operation of waste-to-energy plants when future waste composition is uncertain

Optimal location and operation of waste-to-energy plants when future waste composition is uncertain

Location of Urban Logistics Spaces (ULS) for Two-Echelon Distribution Systems

Designing dynamic reverse logistics network for post-sale service

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