A Modified Priority-Based Encoding for Design of a Closed-Loop Supply Chain Network Using a Discrete League Championship Algorithm

Abstract

In a closed-loop supply chain network, the aim is to ensure a smooth flow of materials and attaining the maximum value from returning and end-of-life goods. This paper presents a single-objective deterministic mixed integer linear programming (MILP) model for the closed-loop supply chain (CLSC) network design problem consisting of plants, collection centers, disposal centers, and customer zones. Our model minimizes the total costs comprising fixed opening cost of plants, collection, disposal centers, and transportation costs of products among the nodes. As supply chain network design problems belong to the class of NP-hard problems, a novel league championship algorithm (LCA) with a modified priority-based encoding is applied to find a near-optimal solution. New operators are defined for the LCA to search the discrete space. Numerical comparison of our proposed encoding with the existing approaches in the literature is indicative of the high quality performance of the proposed encoding.

A Review on Remanufacturing Reverse Logistics Network Design and Model Optimization

“…The meta-heuristic algorithm is mainly used to prevent the search from falling into the local optimal prematurely. The papers adopting the (meta-) heuristic algorithm include: the genetic algorithm (GA) [35,40,42,47,54,55,66,76,81,86,98,118,122,137,138], imperialist competition algorithm (ICA) [2,7], cuckoo optimization algorithm (COA) [48], tabu search [52,102], league championship algorithm (LCA) [114], seeker optimization algorithm (SOA) [111,120], artificial bee colony algorithm (ABCA), the ant colony optimization (ACO) approach [89], particle swarm optimization (PSO) algorithm [73], complex evolution algorithm (CEA) [139], simulated annealing (SA) algorithm [140] and artificial immune system (AIS) algorithm [58].…”

“…Other constraints are maximum number of facilities refs. [ There are constraints on proportion in some of the reviewed papers, including, e.g., the proportions of waste products in the recovery process [38,83,97,[109][110][111][112][113], disposal [34,42,50,61,78,83,92,93,95,[114][115][116][117], remanufacturing [62,65,82,110] and other procedures [56,63,64,90,[118][119][120][121][122][123]. When multiple products are concerned, there are also constraints of demand proportion of each product [53,113] and the distribution proportion of each part after disassembly [55].…”

Designing and Solving Location-Routing-Allocation Problems in a Sustainable Blood Supply Chain Network of Blood Transport in Uncertainty Conditions

“…Constraints ( 17) and ( 18) indicate the transfer of blood bags between the central laboratory centers according to the demand of the customer centers and the perishability time. Constraints (19) and (20) show the equilibrium relationship at the central laboratory centers and ensures that the blood bags are transferred to demand points before the period of blood corruptions. Constraints (21) to (23) are related to the capacity constraints of the temporary blood transfusion centers, the central laboratory centers and permanent blood transfusion centers, and ensure that the center cannot be used until the center has been established.…”

A robust fuzzy mathematical programming model for the closed-loop supply chain network design and a whale optimization solution algorithm

“…Amin and Zhang (2013b) apply theconstraint approach and used a numerical illustration of Copiers Industry to show the applicability of the proposed model. Among the most recent studies, Amin and Baki (2017) propose a multi-objective MIP by considering global factors like exchange rates and customs duties under an uncertain demand pattern and develop a fuzzy solution Ghahremani Nahr et al (2018) investigate a CLSC and propose a so called League Champion meta-heuristic algorithm in their solution approach. Alamdar et al (2018) investigate the optimal decisions in CLSC under a fuzzy price and sales effortdependent demand.…”