Physarum solver: a bio-inspired method for sustainable supply chain network design problem

Abstract

A supplier of products and services aims to minimize the capacity investment cost and the operational cost incurred by unwanted byproducts, e.g. carbon dioxide emission. In this paper, we consider a sustainable supply chain network design problem, where the capacity and the product flow along each link are design variables. We formulate it as a multi-criteria optimization problem. A bio-inspired algorithm is developed to tackle this problem. We illustrate how to design a sustainable supply chain network in three steps. First, we develop a generalized model inspired by the foraging behaviour of slime mould Physarum polycephalum to handle the network optimization with multiple sinks. Second, we propose a strategy to update the link cost iteratively, thus making the Physarum model to converge to a user equilibrium. Third, we perform an equivalent operation to transform a system optimum problem into a corresponding user equilibrium problem so that it is solvable in the Physarum model. The efficiency of the proposed algorithm is illustrated with numerical examples.

Research developments in sustainable supply chain management considering optimization and industry 4.0 techniques: a systematic review

“…Frequently occurring themes coming under I4 cluster include Artificial Intelligence (Ethirajan et al, 2020) and Big Data Analytics (Jain et al, 2022), Internet of things (IoT) (Manavalan and Jayakrishna, 2019), Blockchain (Mangla et al, 2022), Digitalization (Belhadi et al, 2022) and Data-driven decision-making (Zhang et al, 2017).…”

An evaluation of three DoE-guided meta-heuristic-based solution methods for a three-echelon sustainable distribution network

“…Chaabane et al (2012) propose a sustainable SC using a mixed-integer linear programming that provides some underpinning of optimal SC strategies. Zhang et al (2017) report a multi-criteria optimisation model and propose a bio-inspired algorithm to design a sustainable supply chain (SC) network. Varsei and Polyakovskiy (2017) propose a multi-objective mixed-integer programing model to design a sustainable SC.…”

Emergent computing and its applications

“…Such patterns and properties can be further utilised in the design of complex computing systems, smart robotics, large-scale integrated circuits, etc. Being a novel computational paradigm, emergent computation has received ever-increasing attentions and demonstrated promising performance in tackling state-of-the-art optimisation problems over the past decades [1][2][3][4][5].…”