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

This article presents an effective solution method for a two-layer, NP-hard sustainable supply chain distribution model. A DoE-guided MOGA-II optimiser based solution method is proposed for locating a set of non-dominated solutions distributed along the Pareto frontier. The solution method allows decision-makers to prioritise the realistic solutions, while focusing on alternate transportation scenarios. The solution method has been implemented for the case of an Irish dairy processing industry׳s two-layer supply chain network. The DoE generates 6100 real feasible solutions after 100 generations of the MOGA-II optimiser which are then refined using statistical experimentation. As the decision-maker is presented with a choice of several distribution routes on the demand side of the two-layer network, TOPSIS is applied to rank the set of non-dominated solutions thus facilitating the selection of the best sustainable distribution route. The solution method characterises the Pareto solutions from disparate scenarios through numerical and statistical experimentations. A set of realistic routes from plants to consumers is derived and mapped which minimises total CO2 emissions and costs where it can be seen that the solution method outperforms existing solution methods

Sustainable distribution system design: a two-phase DoE-guided meta-heuristic solution approach for a three-echelon bi-objective AHP-integrated location-routing model

This article introduces a sustainable integrated bi-objective location-routing model, its two-phase solution approach and an analysis procedure for the distribution side of three-echelon logistics networks. The mixed-integer programming model captures several real-world factors by introducing an additional objective function and a set of new constraints in the model that outbound logistics channels find difficult to reconcile. The sustainable model minimises CO2 emissions from transportation and total costs incurred in facilities and the transportation channels. Design of Experiment (DoE) is integrated to the meta-heuristic based optimiser to solve the model in two phases. The DoE-guided solution approach enables the optimiser to offer the best stable solution space by taking out solutions with poor design features from the space and refining the feasible solutions using a convergence algorithm thereby selecting the realistic results. Several alternative solution scenarios are obtained by prioritising and ranking the realistic solution sets through a multi-attribute decision analysis tool, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The robust model provides the decision maker the ability to take decisions on sustainable open alternative optimal routes. The outcomes of this research provide theoretical and methodological contributions, in terms of integrated bi-objective location-routing model and its two-phase DoE-guided meta-heuristic solution approach, for the distribution side of three-echelon logistics networks

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

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

This article evaluates the efficiency of three meta-heuristic optimiser (viz. MOGA-II, MOPSO and NSGA-II)-based solution methods for designing a sustainable three-echelon distribution network. The distribution network employs a bi-objective location-routing model. Due to the mathematically NP-hard nature of the model a multi-disciplinary optimisation commercial platform, modeFRONTIER®, is adopted to utilise the solution methods. The proposed Design of Experiment (DoE)-guided solution methods are of two phased that solve the NP-hard model to attain minimal total costs and total CO2 emission from transportation. Convergence of the optimisers are tested and compared. Ranking of the realistic results are examined using Pareto frontiers and the Technique for Order Preference by Similarity to Ideal Solution approach, followed by determination of the optimal transportation routes. A case of an Irish dairy processing industry’s three-echelon logistics network is considered to validate the solution methods. The results obtained through the proposed methods provide information on open/closed distribution centres (DCs), vehicle routing patterns connecting plants to DCs, open DCs to retailers and retailers to retailers, and number of trucks required in each route to transport the products. It is found that the DoE-guided NSGA-II optimiser based solution is more efficient when compared with the DoE-guided MOGA-II and MOPSO optimiser based solution methods in solving the bi-objective NP-hard three-echelon sustainable model. This efficient solution method enable managers to structure the physical distribution network on the demand side of a logistics network, minimising total cost and total CO2 emission from transportation while satisfying all operational constraints

A case analysis of a sustainable food supply chain distribution system—A multi-objective approach

Sustainable supply chain management is a topical area which is continuing to grow and evolve. Within supply chains, downstream distribution from producers to customers plays a significant role in the environmental performance of production supply chains. With consumer consciousness growing in the area of sustainable food supply, food distribution needs to embrace and adapt to improve its environmental performance, while still remaining economically competitive. With a particular focus on the dairy industry, a robust solution approach is presented for the design of a capacitated distribution network for a two-layer supply chain involved in the distribution of milk in Ireland. In particular the green multiobjective optimisation model minimises CO2 emissions from transportation and total costs in the distribution chain. These distribution channels are analysed to ensure the non-dominated solutions are distributed along the Pareto fronts. A multi-attribute decision-making approach, TOPSIS, has been used to rank the realistic feasible transportation routes resulting from the trade-offs between total costs and CO2 emissions. The refined realistic solution space allows the decision-makers to geographically locate the sustainable transportation routes. In addition to geographical mapping the decision maker is also presented with a number of alternative analysed scenarios which forcibly open closed distribution routes to build resiliency into the solution approach. In terms of model performance, three separate GA based optimisers have been evaluated and reported upon. In the case presented NSGA-II was found to outperform its counterparts of MOGA-II and HYBRID

Environmentally Concerned Logistics Operations in Fuzzy Environment: A Literature Survey

Growing environmental awareness coupled with stricter governmental regulations has fueled the need for integrating sustainability into supply chain and logistics activities. Accordingly, recent studies in the literature have emphasized the significance of environmentally concerned logistics operations (ECLO). Research in the broad area of ECLO encompasses a wide range of topics including sustainable supply chain, green supply chain, closed-loop supply chain, low-carbon logistics, and waste management. In this paper, a comprehensive content analysis and area review is presented. Over 800 papers published between 1994 and 2017 in peer-reviewed journals, proceedings, and book chapters are utilized. These papers are analyzed in consecutive stages after being reviewed under a structural dimension process that addresses the fields of environmentally concerned logistics operations. Following the state-of-the-art review, a detailed analysis of ECLO research with a special emphasis on fuzzy applications is provided. The findings clearly indicate that the fuzzy multi-criteria decision making technique is a frequently used hybrid method, whereas fuzzy sets theory and other fuzzy hybrid techniques identify a gap in the related literature. This paper provides further critical analysis and other research suggestions in order to clarify these gaps and offer additional research perspectives. This information may provide extensive data that will enable future researchers to fill these gaps within this field.https://doi.org/10.3390/logistics101000

Logistiikan päätökset ja menetelmät päätöksenteon tukena

Tutkimus käsittelee toimitusketjujen hallintaa, sen työkaluja ja nykytilaa. Viitekehyksenä toimitusketjujen hallinnan tarkastelulle ovat logistiikan päätökset ja niissä käytettävät päätöksenteon tuen menetelmät. Toimitusketjujen hallinnasta on tullut organisaatioille merkittävä keino hankkia kilpailuetua ja lisätä asiakastyytyväisyyttä. Logistiikan päätöksiä tehdään osana toimitusketjujen hallintaa ja ne voivat aiheuttaa merkittäviä muutoksia toimitusketjuihin. Toimitusketjut ovat monimutkaistuneet viime vuosikymmeninä. Tämä on entisestään vaikeuttanut niihin liittyvää päätöksentekoa. Toimitusketjuihin liittyvää päätöksenteon tukea on tutkittu runsaasti 2010-luvulla. Puolustusvoimien toimitusketjut ja sitä kautta logistiikkajärjestelmä koostuu osin siviilikomponentista. Tästä johtuen siviililogistiikan seuraaminen on tärkeä osa Puolustusvoimien logistiikan kehittämistä. Tutkimuksessa kartoitetaan siviililogistiikassa käytettyjä päätöksenteon tuen menetelmiä. Tutkimus tähtää Puolustusvoimallisen siviililogistiikkaa käsittelevän tutkimuspohjan laajentamiseen. Tutkimuksen päätutkimuskysymyksenä on: Millaisia ovat siviilikomponentissa käytetyt logistiikan päätöksenteon tuen menetelmät? Apututkimuskysymyksinä ovat: 1) Mitä päätöksiä varten päätöksenteon tuen menetelmiä on kehitetty? 2) Mitä menetelmiä käytetään minkäkin päätöksen tekemisen tukena? Tutkimusmenetelmänä on systemaattinen kirjallisuuskatsaus, jolla selvitetään siviililogistiikassa käytettäviä päätöksenteon tuen menetelmiä. Teorialuvuissa taustoitetaan tutkimusongelmaa käyttäen menetelmänä kuvailevaa kirjallisuuskatsausta. Työssä kartoitetaan logistiikan päätöksiä ja päätöksen-teon tukea ilmiöinä. Systemaattinen kirjallisuuskatsaus toteutetaan Finkin-mallin mukaisesti. Tutkimusaineisto koostuu Scopus-tietokannasta löytyvistä, vuosina 2017–2021 julkaistuista vertaisarvioiduista artikkeleista. Systemaattisella kirjallisuuskatsauksella vastataan tutkimuksen apututkimuskysymyksiin ja tuetaan päätutkimuskysymykseen vastaamisessa. Tutkimuksen perusteella päätöksenteon tuen menetelmät ovat keskittyneet kumppaneiden valintaan sekä toimitusketjujen rakenteen suunnitteluun. Päätöksenteon tukena käytetään pääasiasiallisesti erilaisia monikriteerisen päätösanalyysin sekä matemaattisen mallinnuksen ja optimoinnin menetelmiä. Päätöksenteossa korostuu tutkimuksen perusteella kestävän kehityksen mukaisten arvojen huomioiminen sekä resilienssin kasvattaminen toimitusketjuissa. Edelleen myös kustannusten minimointi ja tuoton maksimointi ovat säilyneet merkittävinä ajureina päätöksenteossa