Integrated low-carbon distribution system for the demand side of a product distribution supply chain: a DoE-guided MOPSO optimiser-based solution approach

Abstract

This article contributes to location-routing literature on three inter-linked aspects viz., formulation of a novel integrated low-carbon/green location-routing model for the demand side of a Supply Chain (SC) with a single product and multiple consumers, i.e., Drop-off Points (DoPs), a novel and robust solution approach through a Design of Experiment (DoE)-guided Multiple-Objective Particle Swarm Optimisation (MOPSO) optimiser and exhaustive analysis of the location-routing solutions (i.e., prioritisation, ranking and scenario analysis). The total costs, CO 2 emission and the traversed distances of the vehicles during transportation are optimised. The optimisation model for the strategic decision-making is formulated by effectively integrating the 0-1 mixed-integer programming with a green constraint based on Analytic Hierarchy Process (AHP). Due to the computationally NP-hard characteristic of the model a systematic and technically robust DoE-guided solution approach is designed using a commercial solver -modeFRONTIER ® .DoE guides the solution through the MOPSO optimiser in order to eliminate the un-realistic set of feasible and optimal solution sets. A popular multi-attribute decision-making approach, TOPSIS, evaluates the solutions found from the Pareto optimal solution space of the solver. Finally decision-makers' preferences are analysed for monitoring the changes in the controlling parameters with respect to the changes in the decisions. A scenario analysis of the location-routing events by considering alternative possible outcomes is also conducted. It is found that the implemented methodology successfully routes the vehicles with optimal costs and low-carbon emission thus contributing to greening the environment on the demand side of a SC network.

Environmental Sustainability and Energy-Efficient Supply Chain Management: A Review of Research Trends and Proposed Guidelines

“…Pullman et al [92] reveal that an improvement of environmental performances leads to an improvement of products and services quality, which, in turn, improves cost performances. Validi et al [143] provide a mathematical model to select the shortest path allowing to reduce environmental harmful emission in the field of food supply chain. Yang et al [144] carry out a survey and apply a structural equation model to demonstrate that the adoption of energy-efficient and green practices positively impacts on competitiveness.…”

A solution method for a two-layer sustainable supply chain distribution model

“…The model explores the design space, performs a "rough" optimisation using "search" algorithms based on the designs and refines the feasible solutions using a converging algorithm. The MOGA-II algorithm is used in order to achieve fast Pareto convergence, in executing the low-carbon two-layer model of Validi et al (2014) and Validi (2014). The solution method (Figs.…”

“…A mixed integer linear programming technique is reported in Erdoğan and Miller-Hooks (2012) for tackling a green-vehicle routing problem, and an optimised solution to a multi-objective distribution problem is reported in Validi, (2014), Validi et al (2014) and Validi et al (2012). However, literature on DoE-guided robust and efficient solution methods for low-carbon distribution system models is scant.…”

“…These counties are: Louth, Longford, Meath, West-Meath, Offaly, Kildare, Laois, Wicklow, South Tipperary, North Tipperary, Waterford, Kilkenny, Wexford, Dublin, Monaghan and Cavan. The cost of serving each of these routes is the sum of fuel costs and driver's wage (Validi 2014;Validi et al 2014). Processing plants and the retailers are on the demand side of this supply chain.…”

“…One 'unit' refers to a two-litre carton of milk. It is assumed that milk consumption is proportional to the overall population of each of the twenty-two cities/towns located in the sixteen counties and is consider as 2/3 of the population at each location (Validi 2014;Validi et al 2014). …”