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

Strategies for dynamic appointment making by container terminals

We consider a container terminal that has to make appointments with barges dynamically, in real-time, and partly automatic. The challenge for the terminal is to make appointments with only limited knowledge about future arriving barges, and in the view of uncertainty and disturbances, such as uncertain arrival and handling times, as well as cancellations and no-shows. We illustrate this problem using an innovative implementation project which is currently running in the Port of Rotterdam. This project aims to align barge rotations and terminal quay schedules by means of a multi-agent system. In this\ud paper, we take the perspective of a single terminal that will participate in this planning system, and focus on the decision making capabilities of its intelligent agent. We focus on the question how the terminal operator can optimize, on an operational level, the utilization of its quay resources, while making reliable appointments with barges, i.e., with a guaranteed departure time. We explore two approaches: (i) an analytical approach based on the value of having certain intervals within the schedule and (ii) an approach based on sources of exibility that are naturally available to the terminal. We use simulation to get insight in the benefits of these approaches. We conclude that a major increase in utilization degree could be achieved only by deploying the sources of exibility, without harming the waiting time of barges too much

Destocking, the bullwhip effect, and the credit crisis : empirical modeling of supply chain dynamics

In this paper we analyze the strong sales dip observed in the manufacturing industry at the end of 2008, following the bankruptcy of Lehman Brothers and the subsequent collapse of the financial world. We suggest that firms’ desire to retain liquidity during these times prompted a reaction characterized by the reduction of working capital, which materialized as a synchronized reduction in target inventory levels across industries. We hypothesize that such a reaction effectively acted as an endogenous shock to supply chains, ultimately resulting in the demand dynamics observed. To test this proposition we develop a system dynamics model that explicitly takes into account structural, operational, and behavioral parameters of supply chains aggregated at an echelon level. We calibrate the model for use in 4 different business units of a major chemical company in the Netherlands, all situated 4 to 5 levels upstream from consumer demands in their respective supply chains. We show that the model gives both a very good historical fit and a prediction of the sales developments during the period following the Lehman collapse. We test the model’s robustness to behavioral parameter estimation errors through sensitivity analysis, and provide a comparison with experimental studies based on the ‘beer game’. We observe that the empirical data is aligned with experimental observations regarding the underestimation of the supply pipeline

Modeling location-allocation of military items to the depots without branch classification

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent University, 2002.Thesis (Master's) -- Bilkent University, 2002.Includes bibliographical references leaves 47-49.Işılak, Ali SezginM.S