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Purpose: The purpose of this study is to develop a holistic optimization model for an integrated sustainable fleet planning and closed-loop supply chain (CLSC) network design problem under uncertainty. Design/methodology/approach: A novel mixed-integer programming model that is able to consider interactions between vehicle fleet planning and CLSC network design problems is first developed. Uncertainties of the product demand and return fractions of the end-of-life products are handled by a chance-constrained stochastic program. Several Pareto optimal solutions are generated for the conflicting sustainability objectives via compromise and fuzzy goal programming (FGP) approaches. Findings: The proposed model is tested on a real-life lead/acid battery recovery system. By using the proposed model, sustainable fleet plans that provide a smaller fleet size, fewer empty vehicle repositions, minimal CO2 emissions, maximal vehicle safety ratings and minimal injury/illness incidence rate of transport accidents are generated. Furthermore, an environmentally and socially conscious CLSC network with maximal job creation in the less developed regions, minimal lost days resulting from the work's damages during manufacturing/recycling operations and maximal collection/recovery of end-of-life products is also designed. Originality/value: Unlike the classical network design models, vehicle fleet planning decisions such as fleet sizing/composition, fleet assignment, vehicle inventory control, empty repositioning, etc. are also considered while designing a sustainable CLSC network. In addition to sustainability indicators in the network design, sustainability factors in fleet management are also handled. To the best of the authors' knowledge, there is no similar paper in the literature that proposes such a holistic optimization model for integrated sustainable fleet planning and CLSC network design. [ABSTRACT FROM AUTHOR]

Significant environmental problems have been caused by the growth in the volume of used tires each year. In addition, remanufacturing and recycling options related to the end of life for tires are crucial issues at present because of difficulties related to the degradation of these scrap tires in the environment and the economic benefits of material and energy recovery. Thus, effective collection, storage, recycling, and appropriate disposal methods are required for used tires without damaging the environment by designing an efficient closed-loop supply chain network. Based on this motivation, we present a holistic modeling approach for a tire closed-loop supply chain using mixed integer linear programming. Alternative recovery options such as remanufacturing, recycling, and energy recovery are considered simultaneously in the model. The main objective of this study was to develop a multi-objective, multi-echelon, multi-product, and multi-period logistics network design model in a more holistic manner while also considering environmental issues. To quantify the environmental impact and the closed-loop supply chain, we used a life cycle assessment-based and damage-oriented method (eco-indicator 99). We applied the model to an illustrative case study and an interactive fuzzy goal programming approach was utilized to solve the proposed fuzzy multiple-objective network optimization model. In order to obtain the best profit values and to satisfy the environmental indicator targets, we examined the effects of some parameters (factors) within the profit and damage function using an experimental technique based on the Taguchi design. Experimental runs were conducted using the optimization solver in ILOG OPL Studio 6.3 and the results were evaluated based on Taguchi’s (S/N) ratios, analysis of means graphs, interaction graphs, and analysis of variance with MINITAB 14. [ABSTRACT FROM AUTHOR]

Recent years, there has been a growing interest in reverse logistics, recycling, remanufacturing, and reusing due to the environmental concerns, economical issues, and legal obligations. Companies should take into account the recovery options such as recycling, remanufacturing, etc. while preparing their tactical plans. In this paper, a mixed integer linear programming model is proposed for tactical planning in a conceptual closed-loop supply chain with remanufacturing option. In the model, both forward and reverse flows are involved and two production alternatives are considered: either production of new products directly in manufacturing plants or bringing the returned products back to 'as new condition' in the remanufacturing facilities. The proposed model attempts to optimize all of the consecutive stages in the closed-loop supply chain. Hence, the purpose of this research is to formulate a mathematical programming model to focus primarily on integrating remanufacturing as a recovery option into tactical planning process. The proposed model is applied to an illustrative case and solved by LINGO 9.0 optimization solver. In order to obtain the best objective function value that is targeted, the effects of the major factors regarding reverse flows and remanufacturing system are examined with the help of Taguchi experimental design technique at the end of the study. Analysis of variance, Taguchi's signal/noise ratios, analysis of means graphs and interaction graphs are provided by MINITAB 14 software and interpreted for the evaluation of experimental results and effects of related factors. [ABSTRACT FROM AUTHOR]

Nowadays, there has been a growing interest in reverse logistics, recycling, remanufacturing and reusing due to the environmental, economical issues and legal obligations. Due to this fact, companies should take into account the remanufacturing option while preparing the medium term planning (MTP) activities instead of using traditional production planning models. There are lots of studies in the literature related to the reverse logistics (RL) and closed-loop supply chain (CLSC) network design problem which takes place in strategic planning level but a few of them handles the medium-term planning activities. Thus, a fuzzy mixed integer programming model for medium-term planning in a CLSC related to a conceptual product with remanufacturing option is developed in this paper. In the proposed model, both forward and reverse flows are included and two production alternatives are considered: either 'production of new products directly in manufacturing plants' or 'bringing the returned products back to 'as new condition' in the remanufacturing facilities'. However, real world closed-loop supply chains are surrounded with uncertainty. Thus, storage capacities, retailers' and wholesalers' demands, return rates, acceptance ratios, weekly available production/remanufacturing times, transportation upper bounds and objective function value are considered as fuzzy in the proposed model. The proposed fuzzy mathematical programming model is converted into a crisp equivalent model by utilizing several fuzzy aggregation procedures from the literature. The proposed model is applied to an illustrative case and scenario analysis is also carried out for evaluating the effects of some parameters related to the concerned collection-recovery system. Solution of the proposed model is achieved by using ILOG OPL Studio 6.3. [ABSTRACT FROM AUTHOR]