scholarly journals Transfer Coordination for Metro Networks during the Start- or End-of-Service Period

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Liqiao Ning ◽  
Peng Zhao ◽  
Wenkai Xu ◽  
Ke Qiao
Keyword(s):  
Integer Programming ◽  
Adverse Effects ◽  
Waiting Time ◽  
Programming Model ◽  
Mixed Integer ◽  
Service Period ◽  
Proposed Model ◽  
Transfer Success ◽  
Metro Networks

When travelling via metro networks during the start- or end-of-service period, transferring passengers may suffer a transfer failure. Accordingly, the synchronization timetabling problem necessitates consideration of transfer waiting time and transfer availability with respect to the first or last train. Hence, transfer train index (TTI) is formulated to identify the transfer train and calculate the transfer waiting time. Furthermore, two types of connection indexes, the last connection train index (LCTI) and the first connection train index (FCTI), are devised to distinguish transfer failure from transfer success, and the penalty constraints are implemented together to reflect the adverse effects of transfer failure. Then, a mixed integer programming model is developed to concurrently reduce transfer waiting time and improve transfer availability, which can be solved by CPLEX. Finally, a case study on Beijing metro network is made to verify the method. Experimental results show that our proposed model can yield synchronization solutions with significant reductions in both the average transfer waiting time and the proportion of transfer failure passengers.

scholarly journals A Data-Driven Hybrid Three-Stage Framework for Hospital Bed Allocation: A Case Study in a Large Tertiary Hospital in China

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Li Luo ◽  
Jialing Li ◽  
Xueru Xu ◽  
Wenwu Shen ◽  
Lin Xiao
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Model ◽  
Tertiary Hospital ◽  
Data Driven ◽  
Mixed Integer ◽  
Hospital Bed ◽  
Tertiary Hospitals ◽  
Bed Allocation

Beds are key, scarce medical resources in hospitals. The bed occupancy rate (BOR) amongst different departments within large tertiary hospitals is very imbalanced, a situation which has led to problems between the supply of and the demand for bed resources. This study aims to balance the utilization of existing beds in a large tertiary hospital in China. We developed a data-driven hybrid three-stage framework incorporating data analysis, simulation, and mixed integer programming to minimize the gaps in BOR among different departments. The first stage is to calculate the length of stay (LOS) and BOR of each department and identify the departments that need to be allocated beds. In the second stage, we used a fitted arrival distribution and median LOS as the input to a generic simulation model. In the third stage, we built a mixed integer programming model using the results obtained in the first two stages to generate the optimal bed allocation strategy for different departments. The value of the objective function, Z, represents the severity of the imbalance in BOR. Our case study demonstrated the effectiveness of the proposed data-driven hybrid three-stage framework. The results show that Z decreases from 0.7344 to 0.0409 after re-allocation, which means that the internal imbalance has eased. Our framework provides hospital bed policy makers with a feasible solution for bed allocation.

scholarly journals The unit train make-up scheme for loaded direction in the heavy haul railway

2019 ◽  
Vol 1 (1) ◽  
pp. 30-44 ◽  
Author(s):  
Yuqiang Wang ◽  
Yuguang Wei ◽  
Hua Shi ◽  
Xinyu Liu ◽  
Liyuan Feng ◽  
...  
Keyword(s):  
Integer Programming ◽  
Design Methodology ◽  
Arrival Time ◽  
Programming Model ◽  
Nonlinear Integer Programming ◽  
Content Type ◽  
Proposed Model ◽  
Heavy Haul ◽  
Heavy Haul Railway

Purpose The purpose of this paper is to study the unit train make-up scheme for loaded direction in the heavy haul railway. Design/methodology/approach A 0-1 nonlinear integer programming model with the aim of minimizing the idling period between actual train arrival time and expected train arrival time for all loaded unit trains are proposed. Findings The proposed model is applied into a case study based on Daqin heavy haul railway. Results show that the proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway. Originality/value The proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

scholarly journals OPTIMIZING THE CONTAINER TRUCK PATHS WITH UNCERTAIN TRAVEL TIME IN CONTAINER PORTS

Transport ◽  
2021 ◽  
Vol 36 (6) ◽  
pp. 444-462
Author(s):  
Jiaming Liu ◽  
Bin Yu ◽  
Wenxuan Shan ◽  
Baozhen Yao ◽  
Yao Sun
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Programming Model ◽  
Mixed Integer ◽  
A Algorithm ◽  
Shuffled Complex Evolution ◽  
Proposed Model ◽  
Container Ports ◽  
Yard Template

The yard template problem in container ports determines the assignment of space to store containers for the vessels, which could impact container truck paths. Actually, the travel time of container truck paths is uncertain. This paper considers the uncertainty from two perspectives: (1) the yard congestion in the context of yard truck interruptions, (2) the correlation among adjacent road sections (links). A mixed-integer programming model is proposed to minimize the travel time of container trucks. The reliable shortest path, which takes the correlation among links into account is firstly discussed. To settle the problem, a Shuffled Complex Evolution Approach (SCE-UA) algorithm is designed to work out the assignment of yard template, and the A* algorithm is presented to find the reliable shortest path according to the port operator’s attitude. In our case study, one yard in Dalian (China) container port is chosen to test the applicability of the model. The result shows the proposed model can save 9% of the travel time of container trucks, compared with the model without considering the correlation among adjacent links.

scholarly journals A Bilevel Multiobjective Optimisation Approach for Solving the Evacuation Location Assignment Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Ahmed W. A. Hammad
Keyword(s):  
Assignment Problem ◽  
Programming Model ◽  
Decision Makers ◽  
Mixed Integer ◽  
Multiobjective Optimisation ◽  
Proposed Model ◽  
Level Problem ◽  
Location Assignment ◽  
Optimisation Model

In this paper, a bilevel multiobjective optimisation model is proposed to solve the evacuation location assignment problem. The model incorporates the two decision-makers’ spaces, namely, urban planners and evacuees. In order to solve the proposed problem, it is first reformulated into a single-level problem using the Karush–Kuhn–Tucker conditions. Next, the problem is linearised into a mixed-integer linear programming model and solved using an off-the-shelf solver. A case study is examined to showcase the applicability of the proposed model, which is solved using single-objective and multiobjective lexicographic optimisation approaches. The model provides planners with an ability to determine the best locations for placement of shelters in such a way that the evacuees’ traffic assignment on the existing network is optimised.

Joint Deployment of Quay Cranes and Yard Cranes in Container Terminals at a Tactical Level

2018 ◽  
Vol 2672 (9) ◽  
pp. 35-46
Author(s):  
Lingxiao Wu ◽  
Shuaian Wang
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Model ◽  
Container Terminal ◽  
Turnaround Time ◽  
Container Terminals ◽  
Mixed Integer ◽  
Sequential Method ◽  
Quay Cranes ◽  
Proposed Model

This paper discusses tactical joint quay crane (QC) and yard crane (YC) deployment in container terminals. The deployments of QCs and YCs are critical for the efficiency of container terminals. Although they are closely intertwined, the deployments of QCs and YCs are usually sequential. This paper proposes a mixed-integer programming model for the joint deployment of QCs and YCs in container terminals. The objective of the model is to minimize the weighted vessel turnaround time and the weighted delayed workload for external truck service in yard blocks, both of great importance for a container terminal but rarely considered together in the literature. This paper proves that the studied problem is NP-hard in the strong sense. Case studies demonstrate that the proposed model can obtain better solutions than the sequential method. This paper also investigates the most effective combinations of QCs and YCs for a container terminal at various demand levels.

scholarly journals An Integer Programming Model for Alternative Selection and Planning Stages for Cleaner Production Programs: a Case Study for Greenhouse Gases Reduction

2016 ◽  
Vol 19 (2) ◽  
pp. 5-17
Author(s):  
Thanh Van Tran ◽  
Hai Thanh Le
Keyword(s):  
Integer Programming ◽  
Greenhouse Gases ◽  
Programming Model ◽  
Electricity Consumption ◽  
Cleaner Production ◽  
Waste Reduction ◽  
Integer Programming Model ◽  
Proposed Model ◽  
Selection Of

The selection of subjects (such as waste stream, process, apparatus, ect.) for improvement and development their alternatives when implementing cleaner production (CP) programs at the company in order to achieve the highest efficiency is a complex and timeconsuming process, especially in case when there are many subjects to be improved, and many alternatives for each subject. The problem in this case is which subject and its respective alternative is to be selected in order to obtain maximal waste reduction objective with minimization cost. To solve this problem, this article proposes an optimization mathematical model to support alternatives selection for CP programs. In this study, an integer programming model is applied for defining theselection steps of alternatives and setting the implementing plan within CP program. The proposed model is investigated in a real case study at a cassava starch factory in Tay Ninh, Vietnam (where is the most concentrated area of cassava processing in the country) with purpose to propose the measures for reduction of greenhouse gases (GHGs) and electricity consumption. The results show that this model can be considered as a new effective method for alternative CP selection and planning for CP implementation, especially in case of many subjects and alternatives. The solution of this model can be generalized to apply in any cases with unlimited number of subjects and alternatives.

scholarly journals Effect of prior probabilities on the classificatory performance of parametric and mathematical programming approaches to the two-group discriminant problem

1997 ◽  
Vol 1 (1) ◽  
pp. 45-51 ◽  
Author(s):  
Constantine Loucopoulos
Keyword(s):  
Integer Programming ◽  
Mathematical Programming ◽  
Group Membership ◽  
Programming Model ◽  
Simulated Data ◽  
Parametric Models ◽  
Mixed Integer ◽  
Prior Probabilities ◽  
Normal Populations ◽  
Proposed Model

A mixed-integer programming model (MIP) incorporating prior probabilities for the two-group discriminant problem is presented. Its classificatory performance is compared against that of Fisher's linear discrimininant function (LDF) and Smith's quadradic discriminant function (QDF) for simulated data from normal and nonnormal populations for different settings of the prior probabilities of group membership. The proposed model is shown to outperform both LDF and QDF for most settings of the prior probabilities when the data are generated from nonnormal populations but underperforms the parametric models for data generated from normal populations.

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