scholarly journals A Lexicographic Approach to Postdisaster Relief Logistics Planning Considering Fill Rates and Costs under Uncertainty

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Yajie Liu ◽  
Bo Guo
Keyword(s):  
Stochastic Programming ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Mixed Integer ◽  
Integer Optimization ◽  
Solution Algorithms ◽  
Evacuation Plans ◽  
Proposed Model ◽  
Transportation Assets ◽  
Stochastic Programming Model

Predicting the occurrences of earthquakes is difficult, but because they often bring huge catastrophes, it is necessary to launch relief logistics campaigns soon after they occur. This paper proposes a stochastic optimization model for post-disaster relief logistics to guide the strategic planning with respect to the locations of temporary facilities, the mobilization levels of relief supplies, and the deployment of transportation assets with uncertainty on demands. In addition, delivery plans for relief supplies and evacuation plans for critical population have been developed for each scenario. Two objectives are featured in the proposed model: maximizing the expected minimal fill rate of affected areas, where the mismatching distribution among correlated relief demands is penalized, and minimizing the expected total cost. An approximate lexicographic approach is here used to transform the bi-objective stochastic programming model into a sequence of single objective stochastic programming models, and scenario-decomposition-based heuristic algorithms are furthermore developed to solve these transformed models. The feasibility of the proposed bi-objective stochastic model has been demonstrated empirically, and the effectiveness of the developed solution algorithms has also been evaluated and compared to that of commercial mixed-integer optimization software.

Stochastic Programming Based on Traveling Salesman Problem with Stochastic Cost

2013 ◽  
Vol 321-324 ◽  
pp. 2076-2079
Author(s):  
Xiao Zheng Yang ◽  
Qing Chun Li ◽  
Lei Zhou ◽  
Hong Qi Hui
Keyword(s):  
Stochastic Programming ◽  
Traveling Salesman Problem ◽  
Programming Model ◽  
Real Life ◽  
Traveling Salesman ◽  
Factors Affecting ◽  
Logistics Distribution ◽  
Proposed Model ◽  
Stochastic Programming Model ◽  
Cost Factors

The research of traveling salesman problem (TSP) is important in logistics distribution. Because many stochastic cost factors affecting logistics distribution in real life, a class of stochastic programming model is considered in TSP in this paper. Through given a class of synthesizing effect functions which synthesis expectation and variance of cost factors, stochastic programming model of TSP with stochastic cost can be converted into a class of crisp programming models. A genetic algorithm based on real coding is used in an illustrative example. It is provided to show the effectiveness of the proposed model and method.

scholarly journals Berth Allocation and Quay Crane Assignment Under Uncertainties

2020 ◽  
Author(s):  
Caimao Tan ◽  
Junliang He ◽  
Yuancai Wang
Keyword(s):  
Stochastic Programming ◽  
Numerical Experiments ◽  
Programming Model ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Operations Planning ◽  
Proposed Model ◽  
Departure Time ◽  
Stochastic Programming Model ◽  
Quay Crane Assignment

The integration of berth allocation problem (BAP) and quay crane assignment problem (QCAP) is an cardinal seaside operations planning, which is susceptible to uncertainties, e.g. uncertain vessels arrival and maritime market. This paper addresses the integrated optimization of BAP and QCAP under uncertainties. A stochastic programming model is formulated for minimizing the waiting time and delay departure time of vessels. Besides, numerical experiments and scenario analysis are conducted to validate the effectiveness of the proposed model.

scholarly journals Accounting for Fairness in a Two-Stage Stochastic Programming Model for Kidney Exchange Programs

2018 ◽  
Vol 15 (7) ◽  
pp. 1491 ◽  
Author(s):  
Hyunwoo Lee ◽  
Seokhyun Chung ◽  
Taesu Cheong ◽  
Sang Song
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Deterministic Models ◽  
Two Stage ◽  
Total Utility ◽  
Exchange Programs ◽  
Kidney Exchange ◽  
Second Stage ◽  
Proposed Model ◽  
Stochastic Programming Model

Kidney exchange programs, which allow a potential living donor whose kidney is incompatible with his or her intended recipient to donate a kidney to another patient in return for a kidney that is compatible for their intended recipient, usually aims to maximize the number of possible kidney exchanges or the total utility of the program. However, the fairness of these exchanges is an issue that has often been ignored. In this paper, as a way to overcome the problems arising in previous studies, we take fairness to be the degree to which individual patient-donor pairs feel satisfied, rather than the extent to which the exchange increases social benefits. A kidney exchange has to occur on the basis of the value of the kidneys themselves because the process is similar to bartering. If the matched kidneys are not of the level expected by the patient-donor pairs involved, the match may break and the kidney exchange transplantation may fail. This study attempts to classify possible scenarios for such failures and incorporate these into a stochastic programming framework. We apply a two-stage stochastic programming method using total utility in the first stage and the sum of the penalties for failure in the second stage when an exceptional event occurs. Computational results are provided to demonstrate the improvement of the proposed model compared to that of previous deterministic models.

Optimization of Plane Slots Number for Container Yard Based on Two-Stage Stochastic Programming

2013 ◽  
Vol 807-809 ◽  
pp. 2845-2848
Author(s):  
Zi Jian Guo ◽  
Xu Hui Yu ◽  
Wen Yuan Wang ◽  
Guo Lei Tang
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Random Variable ◽  
Optimization Method ◽  
Low Carbon ◽  
Two Stage ◽  
The Sustainable Development ◽  
Proposed Model ◽  
Container Ports ◽  
Stochastic Programming Model

Appropriate plane slots number of the container yard is of great importance to the sustainable development of low-carbon container ports. Considering the container type, handling process, cost and benefit of unit yard space, etc., a two-stage stochastic programming model with the goal of maximizing the yard profit was established by choosing the maximum daily storage number of containers as a random variable. The maximum yard profit and the minimum penalty function are respectively chosen as the goal in the first and second stage. The example results show that the value obtained by the two-stage stochastic programming is smaller than that by the specification. The proposed model provides an optimization method for the determination of plane slots number through effectively lessening the influence of uncertainties and saving resource cost.

scholarly journals Allocation and Scheduling of Handling Resources in the Railway Container Terminal Based on Crossing Crane Area

2021 ◽  
Vol 13 (3) ◽  
pp. 1190
Author(s):  
Gang Ren ◽  
Xiaohan Wang ◽  
Jiaxin Cai ◽  
Shujuan Guo
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Simultaneous Optimization ◽  
Mixed Integer ◽  
Gantry Crane ◽  
Optimization Scheme ◽  
Long Distance ◽  
Proposed Model ◽  
Hybrid Heuristic Algorithm ◽  
Searching Ability

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.

Cuckoo optimization algorithm in reverse logistics: A network design for COVID-19 waste management

2021 ◽  
pp. 0734242X2110039
Author(s):  
Elham Shadkam
Keyword(s):  
Waste Management ◽  
Network Design ◽  
Optimization Algorithm ◽  
Reverse Logistics ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Fixed Costs ◽  
Logistics System ◽  
Cuckoo Optimization Algorithm ◽  
Proposed Model

Today, reverse logistics (RL) is one of the main activities of supply chain management that covers all physical activities associated with return products (such as collection, recovery, recycling and destruction). In this regard, the designing and proper implementation of RL, in addition to increasing the level of customer satisfaction, reduces inventory and transportation costs. In this paper, in order to minimize the costs associated with fixed costs, material flow costs, and the costs of building potential centres, a complex integer linear programming model for an integrated direct logistics and RL network design is presented. Due to the outbreak of the ongoing global coronavirus pandemic (COVID-19) at the beginning of 2020 and the consequent increase in medical waste, the need for an inverse logistics system to manage waste is strongly felt. Also, due to the worldwide vaccination in the near future, this waste will increase even more and careful management must be done in this regard. For this purpose, the proposed RL model in the field of COVID-19 waste management and especially vaccine waste has been designed. The network consists of three parts – factory, consumers’ and recycling centres – each of which has different sub-parts. Finally, the proposed model is solved using the cuckoo optimization algorithm, which is one of the newest and most powerful meta-heuristic algorithms, and the computational results are presented along with its sensitivity analysis.

A Multi-Period Evacuation Vehicle Routing Problem Model

2014 ◽  
Vol 931-932 ◽  
pp. 578-582
Author(s):  
Sunarin Chanta ◽  
Ornurai Sangsawang
Keyword(s):  
Vehicle Routing ◽  
Public Transportation ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
High Water ◽  
Mixed Integer ◽  
Routing Problem ◽  
Problem Model ◽  
Proposed Model ◽  
Evacuation Routing

In this paper, we proposed an optimization model that addresses the evacuation routing problem for flood disaster when evacuees trying to move from affected areas to safe places using public transportation. A focus is on the situation of evacuating during high water level when special high vehicles are needed. The objective is to minimize the total traveled distance through evacuation periods where a limited number of vehicles is given. We formulated the problem as a mixed integer programming model based on the capacitated vehicle routing problem with multiple evcuation periods where demand changing by the time. The proposed model has been tested on a real-world case study affected by the severe flooding in Thailand, 2011.

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