Robust Multi-Objective Sustainable Reverse Supply Chain Planning: An Application in the Steel Industry

In the design of the supply chain, the use of the returned products and their recycling in the production and consumption network is called reverse logistics. The proposed model aims to optimize the flow of materials in the supply chain network (SCN), and determine the amount and location of facilities and the planning of transportation in conditions of demand uncertainty. Thus, maximizing the total profit of operation, minimizing adverse environmental effects, and maximizing customer and supplier service levels have been considered as the main objectives. Accordingly, finding symmetry (balance) among the profit of operation, the environmental effects and customer and supplier service levels is considered in this research. To deal with the uncertainty of the model, scenario-based robust planning is employed alongside a meta-heuristic algorithm (NSGA-II) to solve the model with actual data from a case study of the steel industry in Iran. The results obtained from the model, solving and validating, compared with actual data indicated that the model could optimize the objectives seamlessly and determine the amount and location of the necessary facilities for the steel industry more appropriately.This article belongs to the Special Issue Uncertain Multi-Criteria Optimization Problem

Empowering citizens' cognition and decision making in smart sustainable cities

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Advances in Internet technologies have made it possible to gather, store, and process large quantities of data, often in real time. When considering smart and sustainable cities, this big data generates useful information and insights to citizens, service providers, and policy makers. Transforming this data into knowledge allows for empowering citizens' cognition as well as supporting decision-making routines. However, several operational and computing issues need to be taken into account: 1) efficient data description and visualization, 2) forecasting citizens behavior, and 3) supporting decision making with intelligent algorithms. This paper identifies several challenges associated with the use of data analytics in smart sustainable cities and proposes the use of hybrid simulation-optimization and machine learning algorithms as an effective approach to empower citizens' cognition and decision making in such ecosystemsPeer ReviewedPostprint (author's final draft

Assessing the sustainability of biomass supply chains for energy exploitation

Biomass use has increased significantly lately, partly due to conventional fuels price increase. This trend is more evident in rural areas with significant local biomass availability. Biomass may be used in various ways to generate heat. In this work, the focus is on comparing two different biomass energy exploitation supply chains that provide heat at a specific number of customers at a specific cost. The first system is pellets production from biomass and distribution of the pellets to the final customers for use in domestic pellet boilers. The second option is centralized energy co-generation, which entails simultaneous electricity and heat generation. In the latter case, heat is distributed to the customers via a district heating network whereas electricity is fed to the electricity grid. The biomass source examined is locally available agricultural residues and the model is applied to a case study region in Greece. The aim of this work is to determine how these two different biomass exploitation options perform in sustainability terms, including the economic, environmental and social dimensions of sustainability. The effect of trying to optimise separately the economic and environmental dimensions of sustainability on the system design is examined, while at the same time taking into account the social dimension. Furthermore, a bi-objective optimisation is employed, to overcome the limitations of the single-objective optimisation. Both the upstream and the downstream supply chains of the pelletizing/CHP units are modelled

Evolution of green shipping research: themes and methods

Over the past 30 years, there have been growing concerns on theenvironmental impacts of maritime transportation, which have attractedgreat attention from both academia and practitioners. Understandingdevelopments in this area can help guide future research. We conducteda comprehensive review of green shipping research, comprising 213papers published in transportation journals in SSCI of 2017 over theperiod 1988–2017. We find that research on green shipping hasincreased greatly since 2012, accounting for 77.5% of the reviewedpapers. The main focus today on green shipping was on air pollution,and the classification of green shipping practice, such as technical measures,operational options, market-based measures, and recycling andreusing, is becoming clear. According to the existing studies, futureresearch on green shipping must strengthen technology research tonot only solve practical problems, but also to establish a theoreticalgreen shipping system. Moreover, researchers from different countriescould cooperate with each other to give effective suggestions on settingstandards and laws of green shipping. Finally, we identify the futureresearch themes will focus on setting up green shipping system andlegislation and policy

A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times

Green transportation is becoming relevant in the context of smart cities, where the use of electric vehicles represents a promising strategy to support sustainability policies. However the use of electric vehicles shows some drawbacks as well, such as their limited driving-range capacity. This paper analyses a realistic vehicle routing problem in which both driving-range constraints and stochastic travel times are considered. Thus, the main goal is to minimize the expected time-based cost required to complete the freight distribution plan. In order to design reliable Routing plans, a simheuristic algorithm is proposed. It combines Monte Carlo simulation with a multi-start metaheuristic, which also employs biased-randomization techniques. By including simulation, simheuristics extend the capabilities of metaheuristics to deal with stochastic problems. A series of computational experiments are performed to test our solving approach as well as to analyse the effect of uncertainty on the routing plans.Peer Reviewe

A complex approach for the design, construction and organizational management of logistics storage and products processing centers

Purpose: The introduced article aims at elaborating effective solutions in terms of designing and constructing buildings and objects of a regional logistics center serviced by a 3-4 PL-level provider taking into account practical experience in the design, construction and maintenance of logistics storage and products processing terminals that have been built. Design/Methodology/Approach: The research of the principles of designing logistics centers substantiates the necessity of revealing and working on technological trends in the development of internal logistics along with research and development, infrastructural, planning restrictions, capacity, reserve options. Findings: The best available equipment with the unlimited wide set of features is insufficient; each of these features needs to be applied in the working process as a single supply chain of consecutive actions. Practical implications: The findings of this paper can be used in the practical activities of regional and federal logistics enterprises, by public and commercial entities, in the administrative activities of enterprises and organizations. Originality/value: This research bears its determining significance in its effectiveness of practical functioning of logistics centers.peer-reviewe

On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

A Methodology for Assessing Eco-efficiency in Logistics Networks

Recent literature on sustainable logistics networks points to two important questions: (i) How to spot the preferred solution(s) balancing environmental and business concerns? (ii) How to improve the understanding of the trade-offs between these two dimensions? We posit that a complete exploration of the efficient frontier and trade-offs between profitability and environmental impacts are particularly suitable to answer these two questions. In order to deal with the exponential number of basic efficient points in the frontier, we propose a formulation that performs in exponential time for the number of objective functions only. We illustrate our findings by designing a complex recycling logistics network in Germany.Eco-efficiency;Environmental impacts;Profitability;Recycling logistics network