258 research outputs found

    Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using GRASP method

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    Cross docking play an important role in management of supply chains where items delivered to a warehouse by inbound trucks are directly sorted out, reorganized based on customer demands, routed and loaded into outbound trucks for delivery to customers without virtually keeping them at the warehouse. If any item is held in storage, it is usually for a short time, which is normally less than 24 hours. The proposed model of this paper considers a special case of cross docking where there is temporary storage and uses GRASP technique to solve the resulted problem for some realistic test problems. In our method, we first use some heuristics as initial solutions and then improve the final solution using GRASP method. The preliminary test results indicate that the GRASP method performs better than alternative solution strategies

    Rich Vehicle Routing Problems and Applications

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    Bulk wheat transportation and storage problem of public distribution system

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    This research investigates the multi-period multi-modal bulk wheat transportation and storage problem in a two-stage supply chain network of Public Distribution System (PDS). The bulk transportation and storage can significantly curtail the transit and storage losses of food grains, which leads to substantial cost savings. A mixed integer non-linear programming model (MINLP) is developed after studying the Indian wheat supply chain scenario, where the objective is to minimize the transportation, storage and operational cost of the food grain incurred for efficient transfer of wheat from producing states to consuming states. The cost minimization of Indian food grain supply chain is a very complex and challenging problem because of the involvement of the many entities and their constraints such as seasonal procurement, limited scientific storages, varying demand, mode of transportation and vehicle capacity constraints. To address this complex and challenging problem of food grain supply chain, we have proposed the novel variant of Chemical Reaction Optimization (CRO) algorithm which combines the features of CRO and Tabu search (TS) and named it as a hybrid CROTS algorithm (Chemical reaction optimization combined with Tabu Search). The numerous problems with different sizes are solved using the proposed algorithm and obtained results have been compared with CRO. The comparative study reveals that the proposed CROTS algorithm offers a better solution in less computational time than CRO algorithm and the dominance of CROTS algorithm over the CRO algorithm is demonstrated through statistical analysis

    Internet of Things in urban waste collection

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    Nowadays, the waste collection management has an important role in urban areas. This paper faces this issue and proposes the application of a metaheuristic for the optimization of a weekly schedule and routing of the waste collection activities in an urban area. Differently to several contributions in literature, fixed periodic routes are not imposed. The results significantly improve the performance of the company involved, both in terms of resources used and costs saving

    Optimization Models for Locating Cross-docks under Capacity Uncertainty

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    The objective of this thesis is to develop mathematical models for locating cross-docks in a supply chain. Cross-docking is a strategy which can help consolidate the goods in the supply chain and save costs by reducing the number of truck trips. In this thesis four optimization models were developed. First two optimization models termed Model A and Model B were deterministic models. The goal of model A was to choose exactly P locations to locate cross-docks so that the transportation and handling costs are minimized. The goal of model B is to locate as many cross-docks as needed so that total routing, handling, and facility location costs are minimized. Then we developed a chance constraint model and a recourse model which accounted for capacity uncertainties at cross-dock location. The chance constraint model accounts for day to day operational uncertainties whereas the recourse model accounts to drastic reductions in capacities due to disruptions. Extensive computational analysis was conducted on two networks with parameters consistent with real world freight operations. The results reveal that cross-docking provides significant savings when the demand sizes are small and there is more potential for consolidation. For larger demands where the potential for consolidation is less, cross-dock savings diminish. The results were found to be consistent across a variety of capacity uncertainty scenarios

    A robust solving strategy for the vehicle routing problem with multiple depots and multiple objectives

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    This document presents the development of a robust solving strategy for the Vehicle Routing Problem with Multiple Depots and Multiple Objectives (MO-MDVRP). The problem tackeled in this work is the problem to minimize the total cost and the load imbalance in vehicle routing plan for distribution of goods. This thesis presents a MILP mathematical model and a solution strategy based on a Hybrid Multi- Objective Scatter Search Algorithm. Several experiments using simulated instances were run proving that the proposed method is quite robust, this is shown in execution times (less than 4 minutes for an instance with 8 depots and 300 customers); also, the proposed method showed good results compared to the results found with the MILP model for small instances (up to 20 clients and 2 depots).MaestrĂ­aMagister en IngenierĂ­a Industria
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