scholarly journals Heuristic algorithms applied to the problems of servicing actors in supply chains

2017 ◽  
Vol 44 (4) ◽  
pp. 25-34 ◽  
Author(s):  
Mariusz Izdebski ◽  
Ilona Jacyna-Gołda ◽  
Katarzyna Markowska ◽  
Jakub Murawski

The paper discusses main decision problems analysed in the subject matter of servicing actors operating in the supply chains, i.e. the vehicle routing problem, vehicles-to-task assignment problem and the problem of entities’ localization in the supply chain. The input data used to describe supply chains is given as well as the basic constraints and the criterion functions used in the development of mathematical models describing the supply chains. Servicing actors in supply chains is the complex decision making problem. Operators in the supply chains are constrained by: production capacity of the suppliers, the demand of the customers in particular working days, storage capacities of warehouses, handling capacities of warehouses, suppliers’ and warehouses’ time windows and other. The efficiency of supply chain is described by cost of transport between operators, costs of passing cargoes through warehouses and delivery time to the recipient. The heuristic algorithms, like genetic and ant algorithms are detailed and used to identify issues related to the operation of actors operating in the supply chains are described. These algorithms are used for solving localization problems in supply chains, vehicle routing problems, and assignment problems. The complexity of presented issues (TSP is known as NP-hard problem) limits the use of precise algorithms and implies the need to use heuristic algorithms. It should be noted that solutions generated by these algorithms for complex decision instances are sub-optimal solutions, but nonetheless it is accepted from the practical point of view.

Author(s):  
Yibo Dang ◽  
Manjeet Singh ◽  
Theodore T. Allen

DHL Supply Chain North America moves more than 20 million packages each year. DHL transportation planners perform routing and cost-deduction tasks for many business projects. We refer to the associated planning problem as the Vehicle Routing Problem with Time Regulations and Common Carriers (VRPTRCC). Unlike ordinary vehicle routing problems, which use only a single type of transportation mode, our VRPTRCC applications include make–buy decisions because some of the package deliveries are ultimately subcontracted to organizations other than DHL. Time regulation means that the problem considers not only delivery-time windows, but also layover and driving-time restrictions. Our developed Network Mode Optimization Tool (NMOT) is an ant-colony optimization (ACO)-based program that aids DHL Supply Chain transportation analysts in identifying cost savings in the ground logistic network. By using the NMOT, DHL and its customers have saved millions of dollars annually. Also, the NMOT is helping DHL to win new customers against bidding competitors and reducing estimation times from multiple weeks to hours. The results show an actual increase in profits compared with the previous process by more than 15% through a combination of new projects enabled and reduced current operational costs. The NMOT is implemented and evaluated by using data from ongoing projects.


2008 ◽  
Vol 35 (9) ◽  
pp. 3034-3048 ◽  
Author(s):  
Karl F. Doerner ◽  
Manfred Gronalt ◽  
Richard F. Hartl ◽  
Guenter Kiechle ◽  
Marc Reimann

2019 ◽  
Vol 889 ◽  
pp. 588-596
Author(s):  
Ho Thi Thu Ai ◽  
Nguyen Truong Thi ◽  
Nguyen Van Can

Green transportation has emerged as an efficient way to promote a sustainable supply chain. Transportation activities have significant impact on the whole supply chain at any decision levels. At an operational level, vehicle routing decisions are one of the most critical determinants of the release of transportation emissions. Therefore, this study develops a mathematical model, with an aim to construct routes that simultaneously minimize total cost and total CO2emissions from the transportation activities of a case study located in Can Tho City, Vietnam. A multiple-objective model with the consideration of different vehicle loading capacity, and time windows is then solved using a Weighted Tchebycheff method. Results show that route selection has a positive contribution toward a better balance between economic and environmental objectives.


2019 ◽  
Vol 272 ◽  
pp. 01014
Author(s):  
Gang Chen ◽  
Yan Jiang ◽  
Xing Sheng ◽  
Jingqian Wang ◽  
Hui Jia

The optimization of material distribution is of great importance on shipbuilding project, which determines whether the production capacity of the ship is fully embodied. A workstation-oriented material distribution problem is formulated with reference to the production characteristics of shipyards. This problem can be considered as a complex vehicle routing problem (VRP) with capacity constraints, time windows and multiple distribution centers. In order to minimize the impact of distribution problems on production, a multi-population genetic algorithm (MPGA) that can minimize the sum of earliness and tardiness penalties is proposed in this paper. The proposed algorithm looks for near-optimal solutions for assigning distribution tasks and optimizing vehicle routing. Then, the evaluation of the solutions generated with MPGA is achieved with a priority-based heuristic algorithm. Simulation results of different cases show that the proposed MPGA allows logistics distribution system to operate more efficiently and solutions can be improved by 71% on average compared to those obtained with the traditional priority rule method.


2012 ◽  
Vol 235 ◽  
pp. 356-361
Author(s):  
Jian Hua Wang ◽  
Qiang Mei ◽  
Xian Feng Huang ◽  
Jian Qiang Luo

Agile supply chain must possess the ability of utilizing alliance corporations’ production capacity fully in a systematic view, in order to meet the market demands and its changes quickly and economically. Powerful scheduling techniques are the key support for supply chains’ agility. Based on the discontinuous schedulable periods of suppliers, an agile supply chain static scheduling under schedulable periods (ASCSSSP) of multiple optional suppliers for each part is studied. According to the final product’s supplying BOM, this paper sets up a structural framework model for agile supply chains firstly, then analyzes and builds a mathematic model for the task assignment and schedule optimization of ASCSSSP with the supply-demand time and quantity constraints, and especially designs a novel heuristic algorithm of Task Adjusted by Cost (TAC) to solve the model. Finally, by some numerical experiments, the efficiency and practicability of the model and algorithm is verified by contrasting analysis.


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