Production distribution planning in a multiechelon supply chain using carbon policies: A review and reflections

Sustainability of a supply chain has gained more attention from economists, environmentalists, consumers, manufacturers, government and the academia. In this paper, the literature survey has been performed on production allocation problem in a multi-echelon supply chain with carbon policies. With web-based search engines such as Scopus and Web of Science several resources such as journals, conference proceedings and books are selected and reviewed. It is observed from the literature that the mentioned problem traces the progression of carbon policies in a supply chain over the past 22 years to provide substantiation for Green Supply Chain. The research papers are then analyzed and categorized to construct the useful foundation of previous studies. Moreover, the importance of this problem in recent years needs has been highlighted by mentioning the gaps in the literature. Further, at the end of the paper, several future work directions in this area also suggested.(undefined)info:eu-repo/semantics/publishedVersio

Grain silo location-allocation problem with dwell time for optimization of food grain supply chain network

In the last few decades, production and procurement of food grain in India have steadily increased, however, storage capacity has not increased proportionally. The government of India (GOI) is establishing the various capacitated silos across the country to bridge this storage capacity gap. This paper presents a novel integrated multi-objective, multi-modal and multiperiod mathematical model for grain silo location-allocation problem with Dwell time to support the decision-making process of GOI. Two conflicting objectives- minimization of total supply chain network cost and total lead time (transit and dwell time) are simultaneously optimized using two Pareto based multi-objective algorithms with calibrated parameters

A decision model for a strategic closed-loop supply chain to reclaim End-of-Life Vehicles

Closed-loop supply chain strategies for End-of-Life (EOL) products and their logistics operations have received greater attention in recent years from supply chain research community. These strategies include warranty–based acquisition, quantity–based acquisition, quality–based acquisition, centrally coordinated logistics operations and third-party logistics (3PL) operations. The proposed research integrates two important aspects of an automobile's closed-loop supply chain strategy. The first aspect is optimal transportation planning for raw material parts, newly manufactured and EOL products in a closed-loop supply chain, using demand, collection rate and capacity of associated facilities in the network as functional parameters. We formulated a mixed integer mathematical model for the closed-loop supply chain network with a multi-echelon inventory, multi-period planning and multi-product scenario, which are used to compute the maximum contribution margin generated through different strategies. The second aspect pertains to using the output of the proposed model in first stage to handle the sequential form of a cooperative game. The proposed two–phase decision model analyzes the realization times and delivery limits of different products as an indicator of swapping different strategies. We analyze three instances to understand and validate the applicability of the model. In these scenarios, sensitivity analysis has been performed to demonstrate the robustness of the proposed model. We present managerial insights, leading to flexibility in decision making. It is observed that the demand, collection rate and capacity of network facilities create highly sensitive trilogy for the contribution margin of proposed network. The outcome of this research firstly confers optimal amounts of mass flows in the closed loop supply chain network from a state of the end product (new products, recycled products and non–recycled used products) to a state of the raw material (ferrous metal, non-ferrous metal and shredder fluff). Secondly, authors culminated a confound dichotomy among all reintegration strategies (conveyance, acquisition and cannibalization) by distinct enumeration and quantification (regarding realization times and delivery limits) of each one to forge a robust planning horizon for original equipment manufacturer

Strategic Design of a Robust Supply Chain

The strategic design of a robust supply chain has as goal the configuration of the supply chain structure so that the performance of the supply chain remains of a consistently high quality for all possible future scenarios. We model this goal with an objective function that trades off the central tendency of the supply chain profit with the dispersion of the profit as measured by the standard deviation for any value of the weights assigned to the two components. However, the standard deviation, used as the dispersion penalty for profit maximization, has a square root expression which makes standard maximization algorithms non applicable. The focus in this article is on the development of the strategic and tactical models. The application of the methodology to an industrial case will be reported. The optimization algorithm and detailed numerical experiments will be described in future research

Integrated Location-Production-Distribution Planning in a Multiproducts Supply Chain Network Design Model

This paper proposes integrated location, production, and distribution planning for the supply chain network design which focuses on selecting the appropriate locations to build a new plant and distribution center while deciding the production and distribution of the product. We examine a multiechelon supply chain that includes suppliers, plants, and distribution centers and develop a mathematical model that aims at minimizing the total cost of the supply chain. In particular, the mathematical model considers the decision of how many plants and distribution centers to open and where to open them, as well as the allocation in each echelon. The LINGO software is used to solve the model for some problem cases. The study conducts various numerical experiments to illustrate the applicability of the developed model. Results show that, in small and medium size of problem, the optimal solution can be found using this solver. Sensitivity analysis is also conducted and shows that customer demand parameter has the greatest impact on the optimal solution

Optimization strategies for the integrated management of perishable supply chains: A literature review

Purpose: The main purpose of this article is to systematically review the papers published in the period 2005-2020 about the integration of production, inventory and distribution activities in perishable supply chains. Design/methodology/approach: The proposed research methodology is based on several steps. First, database and keywords are selected, with the aim to search and collect the main papers, dealing with the integration of production, inventory, distribution activities in perishable supply chains. Then, a bibliometric analysis is carried out, to detect: the main publishing sources, the chronological distribution, the most used keywords, the featured authors, about the selected papers. A five-dimension classification framework is proposed to carry out a content analysis, where the papers of the literature review are classified and discussed, according to: supply chain structure, objective, perishability type, solution approach, approach validation. Findings: Interest in the application of optimization models for integrated decision-making along perishable supply chains is strongly growing. Integrating multiple stages of the supply chain into a single framework is complex, especially when referring to perishable products. The vast majority of the problems addressed are then NP-Hard. Only a limited quantity of the selected papers aims to solve real-life case studies. There is a need for further research, which is capable of modeling and quantitatively improving existing supply chains. The potentials of Industry 4.0 are currently little explored. Originality/value: Based on the analysis of the papers published, this article outlines the current state of the art on the optimization strategies for the integrated management of perishable supply chains, which are very complex to be managed. Research trends and gaps are discussed, future challenges are presentedPeer Reviewe

Designing multi-period supply chain network considering risk and emission: a multi-objective approach

This research formulates a multi-objective problem (MOP) for supply chain network (SCN) design by incorporating the issues of social relationship, carbon emissions, and supply chain risks such as disruption and opportunism. The proposed MOP includes three conflicting objectives: maximization of total profit, minimization of supply disruption and opportunism risks, and minimization of carbon emission considering a number of supply chain constraints. Furthermore, this research analyses the effect of social relationship levels between different tiers of SCN on the profitability, risk, and emission over the time. In this regard, we focus on responding to the following questions. (1) How does the evolving social relationship affect the objectives of the supply chain (SC)? (2) How do the upstream firms’ relationships affect the relationships of downstream firms, and how these relationships influence the objectives of the SC? (3) How does the supply disruption risk interact with the opportunism risk through supply chain relationships, and how these risks affect the objectives of the SC? (4) How do these three conflicting objectives trade-off? A Pareto-based multi-objective evolutionary algorithm–non-dominated sorting genetic algorithm-II (NSGA-II) has been employed to solve the presented problem. In order to improve the quality of solutions, tuning parameters of the NSGA-II are modulated using Taguchi approach. An illustrative example is presented to manifest the capability of the model and the algorithm. The results obtained evince the robust performance of the proposed MOP

A Metaheuristic Based Approach for the Customer-Centric Perishable Food Distribution Problem

The CNRST has awarded H. El Raoui an excellence scholarship. D. Pelta acknowledges support from projects TIN2017-86647-P (Spanish Ministry of Economy, Industry, and Competitiveness. Including FEDER funds) and PID2020-112754GB-I00 (Spanish Ministry of Science and Innovation).High transportation costs and poor quality of service are common vulnerabilities in various logistics networks, especially in food distribution. Here we propose a many-objective Customercentric Perishable Food Distribution Problem that focuses on the cost, the quality of the product, and the service level improvement by considering not only time windows but also the customers’ target time and their priority. Recognizing the difficulty of solving such model, we propose a General Variable Neighborhood Search (GVNS) metaheuristic based approach that allows to efficiently solve a subproblem while allowing us to obtain a set of solutions. These solutions are evaluated over some non-optimized criteria and then ranked using an a posteriori approach that requires minimal information about decision maker preferences. The computational results show (a) GVNS achieved same quality solutions as an exact solver (CPLEX) in the subproblem; (b) GVNS can generate a wide number of candidate solutions, and (c) the use of the a posteriori approach makes easy to generate different decision maker profiles which in turn allows to obtain different rankings of the solutions.CNRSTSpanish Ministry of Economy, Industry, and Competitiveness TIN2017-86647-PEuropean Commission TIN2017-86647-PSpanish Government PID2020-112754GB-I0

Network Flexibility for Recourse Considerations in Bi-Criteria Facility Location

What is the best set of facility location decisions for the establishment of a logistics network when it is uncertain how a company’s distribution strategy will evolve? What is the best configuration of a distribution network that will most likely have to be altered in the future? Today’s business environment is turbulent, and operating conditions for firms can take a turn for the worse at any moment. This fact can and often does influence companies to occasionally expand or contract their distribution networks. For most companies operating in this chaotic business environment, there is a continuous struggle between staying cost efficient and supplying adequate service. Establishing a distribution network which is flexible or easily adaptable is the key to survival under these conditions. This research begins to address the problem of locating facilities in a logistics network in the face of an evolving strategic focus through the implicit consideration of the uncertainty of parameters. The trade-off of cost and customer service is thoroughly examined in a series of multi-criteria location problems. Modeling techniques for incorporating service restrictions for facility location in strategic network design are investigated. A flexibility metric is derived for the purposes of quantifying the similarity of a set of non-dominated solutions in strategic network design. Finally, a multi-objective greedy random adaptive search (MOG) metaheuristic is applied to solve a series of bi-criteria, multi-level facility location problems