scholarly journals A Study of Network Violator Interception Based on a Reliable Game Model

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Shi An ◽  
Jianxun Cui ◽  
Meng Zhao ◽  
Jian Wang
Keyword(s):  
Simulated Annealing ◽  
Numerical Experiments ◽  
Programming Model ◽  
Choice Model ◽  
Transportation Network ◽  
Game Model ◽  
Planning Model ◽  
Binary Integer Programming ◽  
Objective Function Values ◽  
Expected Benefits

This study focuses on planning interceptor locations in a general transportation network to maximize the expected benefits from catching violators mixing in public traveler flow. Two reliability-related characteristics are also integrated into the planning model to make it more practical. One is that each interceptor (e.g., a sensor or a checkpoint) has a failure probability. The second is the existence of a “game” between the interceptor planner and violators. A nonlinear nonconvex binary integer programming model is presented. We develop a simulated annealing (SA) algorithm to solve this model, and numerical experiments are conducted to illustrate the computational efficiency of the proposed algorithm. We also analyze the sensitivity of the disruption probability of interceptors to optimal objective function values and discuss how to determine the values of these parameters in a violator route choice model.

Why China must build Sichuan-Tibet railway: From the perspective of regional comprehensive transportation network optimization

2021 ◽  
pp. 1-23
Author(s):  
Junxiang Xu ◽  
Jingni Guo ◽  
Yongdong Sun ◽  
Qiuyu Tang ◽  
Jin Zhang
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Programming Model ◽  
Transportation Network ◽  
Policy Recommendations ◽  
Hub And Spoke ◽  
Passenger Transportation ◽  
The Future ◽  
Annealing Algorithm ◽  
Transportation Organization

We not only firstly applied the theory of hub-and-spoke network to the field of integrated transportation network planning, but also combined our proposed method with Sichuan-Tibet railway, one of super large projects in China, to discuss the optimization and the layout of hub-and-spoke integrated transportation network along the Sichuan-Tibet railway after it is put into operation in the future and put forward some directional policy recommendations. In our study, we have made clear the topological structure of the multi hub and single allocation hybrid hub-and-spoke integrated transportation network in the passenger transportation corridors, established the integer programming model aiming at the minimum generalized travel cost in the network, and we designed the simulated annealing algorithm to solve this problem. In the empirical study, we find that if 5 nodes are selected as hub nodes in hub-and-spoke integrated transportation network, the generalized cost of network travel will be minimized and these specific location of 5 hub nodes can be determined by the selecting principle of hub nodes location, which we proposed in our study. The simulated annealing algorithm can help us to find the connection relationship between nodes. Then we can achieve three types of hub-and-spoke integrated transportation network layout patterns with railway, highway and aviation as the hub nodes. Though further comparative analysis, we find that it is more feasible to choose the integrated transportation network with railway nodes as the hub in transportation organization. Based on this understanding, we put forward policy recommendations on transportation organization to support high-quality planning and operation of integrated transportation network to Sichuan Tibet region in China in the future.

scholarly journals Model and Algorithm for Container Allocation Problem with Random Freight Demands in Synchromodal Transportation

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yan Xu ◽  
Chengxuan Cao ◽  
Bin Jia ◽  
Guangzhi Zang
Keyword(s):  
Hybrid Algorithm ◽  
Numerical Experiments ◽  
Programming Model ◽  
Transportation Network ◽  
Capacity Allocation ◽  
Allocation Problem ◽  
Operational Level ◽  
Proposed Model ◽  
Encode Method ◽  
Effectiveness And Efficiency

This paper aims to investigate container allocation problem with random freight demands in synchromodal transportation network from container carriers’ perspective. Firstly, the problem is formulated as a stochastic integer programming model where the overall objective is to determine a container capacity allocation plan at operational level, so that the expected total transportation profit is maximized. Furthermore, by integrating simulated annealing with genetic algorithm, a problem-oriented hybrid algorithm with a novel gene encode method is designed to solve the optimization model. Some numerical experiments are carried out to demonstrate the effectiveness and efficiency of the proposed model and algorithm.

scholarly journals Reshuffle minimisation to improve storage yard operations efficiency

2021 ◽  
Vol 15 ◽  
pp. 174830262199401
Author(s):  
Hammed Bisira ◽  
Abdellah Salhi
Keyword(s):  
Integer Programming ◽  
Programming Model ◽  
Heuristic Approach ◽  
Container Terminals ◽  
Exact Method ◽  
Computational Results ◽  
Binary Integer Programming ◽  
Integer Programming Model ◽  
Compatibility Test ◽  
Storage Area

There are many ways to measure the efficiency of the storage area management in container terminals. These include minimising the need for container reshuffle especially at the yard level. In this paper, we consider the container reshuffle problem for stacking and retrieving containers. The problem was represented as a binary integer programming model and solved exactly. However, the exact method was not able to return results for large instances. We therefore considered a heuristic approach. A number of heuristics were implemented and compared on static and dynamic reshuffle problems including four new heuristics introduced here. Since heuristics are known to be instance dependent, we proposed a compatibility test to evaluate how well they work when combined to solve a reshuffle problem. Computational results of our methods on realistic instances are reported to be competitive and satisfactory.

scholarly journals Single-Manufacturer Multi-Retailer Supply Chain Models with Discrete Stochastic Demand

2021 ◽  
Vol 13 (15) ◽  
pp. 8271
Author(s):  
Yaqing Xu ◽  
Jiang Zhang ◽  
Zihao Chen ◽  
Yihua Wei
Keyword(s):  
Dynamic Programming ◽  
Supply Chain ◽  
Computational Complexity ◽  
Stackelberg Game ◽  
Programming Model ◽  
Dynamic Programming Method ◽  
Game Model ◽  
Chain Model ◽  
Stochastic Demands ◽  
Demand Models

Although there are highly discrete stochastic demands in practical supply chain problems, they are seldom considered in the research on supply chain systems, especially the single-manufacturer multi-retailer supply chain systems. There are no significant differences between continuous and discrete demand supply chain models, but the solutions for discrete random demand models are more challenging and difficult. This paper studies a supply chain system of a single manufacturer and multiple retailers with discrete stochastic demands. Each retailer faces a random discrete demand, and the manufacturer utilizes different wholesale prices to influence each retailer’s ordering decision. Both Make-To-Order and Make-To-Stock scenarios are considered. For each scenario, the corresponding Stackelberg game model is constructed respectively. By proving a series of theorems, we transfer the solution of the game model into non-linear integer programming model, which can be easily solved by a dynamic programming method. However, with the increase in the number of retailers and the production capacity of manufacturers, the computational complexity of dynamic programming drastically increases due to the Dimension Barrier. Therefore, the Fast Fourier Transform (FFT) approach is introduced, which significantly reduces the computational complexity of solving the supply chain model.

scholarly journals Integrating Dynamic Pricing and Inventory Control for Fresh Agriproduct under Multinomial Logit Choice

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Xiong-zhi Wang ◽  
Wenliang Zhou
Keyword(s):  
Dynamic Pricing ◽  
Programming Model ◽  
Choice Model ◽  
Multinomial Logit ◽  
Linear Ordering ◽  
Stochastic Dynamic ◽  
Inventory Problem ◽  
Numerical Illustration ◽  
Dynamic Stochastic ◽  
Joint Pricing

In this article, we investigate a joint pricing and inventory problem for a retailer selling fresh agriproducts (FAPs) with two-period shelf lifetime in a dynamic stochastic setting, where new and old FAPs are on sale simultaneously. At the beginning of each period the retailer makes ordering decision for new FAP and sets regular and discount price for new and old inventories, respectively. After demand realization, the expired leftover is disposed and unexpired inventory is carried to the next period, continuing selling. Unmet demand of all FAPs is backordered. The objective is to maximize the total expected discount profit over the whole planning horizon. We present a price-dependent, stochastic dynamic programming model taking into account zero lead time, linear ordering costs, inventory holding, and backlogging costs, as well as disposal cost. Considering the influence of the perishability, we integrate a Multinomial Logit (MNL) choice model to describe the consumer behavior on purchasing fresh or nonfresh product. By way of the inverse of the price vector, the original formulation can be transferred to be jointly concave and tractable. Finally we characterize the optimal policy and develop effective methods to solve the problem and conduct a simple numerical illustration.

scholarly journals Integrated Harvest and Farm-to-Door Distribution Scheduling with Postharvest Quality Deterioration for Vegetable Online Retailing

Agronomy ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 724
Author(s):  
Yiping Jiang ◽  
Bei Bian ◽  
Lingling Li
Keyword(s):  
Genetic Algorithm ◽  
Numerical Experiments ◽  
Programming Model ◽  
Time Windows ◽  
Sensitivity Analyses ◽  
Postharvest Quality ◽  
Online Retailing ◽  
Quality Deterioration ◽  
Distribution Scheduling ◽  
Proposed Model

With the rise of vegetable online retailing in recent years, the fulfillment of vegetable online orders has been receiving more and more attention. This paper addresses an integrated optimization model for harvest and farm-to-door distribution scheduling for vegetable online retailing. Firstly, we capture the perishable property of vegetables, and model it as a quadratic postharvest quality deterioration function. Then, we incorporate the postharvest quality deterioration function into the integrated harvest and farm-to-door distribution scheduling and formulate it as a quadratic vehicle routing programming model with time windows. Next, we propose a genetic algorithm with adaptive operators (GAAO) to solve the model. Finally, we carry out numerical experiments to verify the performance of the proposed model and algorithm, and report the results of numerical experiments and sensitivity analyses.

scholarly journals A randomized adaptive trust region line search method

2020 ◽  
Vol 10 (2) ◽  
pp. 259-263
Author(s):  
Saman Babaie-Kafaki ◽  
Saeed Rezaee
Keyword(s):  
Simulated Annealing ◽  
Numerical Experiments ◽  
Line Search ◽  
Optimization Problems ◽  
Trust Region ◽  
Search Method ◽  
Test Problems ◽  
Unconstrained Optimization Problems ◽  
Line Search Method ◽  
Region Line

Hybridizing the trust region, line search and simulated annealing methods, we develop a heuristic algorithm for solving unconstrained optimization problems. We make some numerical experiments on a set of CUTEr test problems to investigate efficiency of the suggested algorithm. The results show that the algorithm is practically promising.

A multi-objective approach to design strategic supply chains and develop responsiveness- efficiency frontiers

2018 ◽  
Vol 29 (1) ◽  
pp. 365-386 ◽  
Author(s):  
Raed AlHusain ◽  
Reza Khorramshahgol
Keyword(s):  
Supply Chain ◽  
Integer Programming ◽  
Programming Model ◽  
Efficient Frontier ◽  
Decision Makers ◽  
Binary Integer Programming ◽  
Content Type ◽  
Strategic Fit ◽  
Cost Efficient ◽  
Alternative Solutions

Purpose The purpose of this paper is twofold. Initially, a multi-objective binary integer programming model is proposed for designing an appropriate supply chain that takes into consideration both responsiveness and efficiency. Then, a responsiveness-cost efficient frontier is generated for the supply chain design that can help organizations find the right balance between responsiveness and efficiency, and hence achieve a strategic fit between organizational strategy and supply chain capabilities. Design/methodology/approach The proposed SC design model used both cross-functional and logistical SC drivers to build a binary integer programming model. To this end, various alternative solutions that correspond to different SC design portfolios were generated and a responsiveness-cost efficient frontier was constructed. Findings Various alternative solutions that correspond to different SC designs were generated and a responsiveness-cost efficient frontier was constructed to help the decision makers to design SC portfolios to achieve a strategic fit between organizational strategy and SC capabilities. Practical implications The proposed methodology enables the decision makers to incorporate both qualitative and quantitative judgements in SC design. The methodology is easy to use and it can be readily implemented by a software. Originality/value The proposed methodology allows for subjective value judgements of the decision makers to be considered in SC design and the efficiency-responsiveness frontier generated by the methodology provides a trade-off to be used when choosing between speed and cost efficiency in SC design.

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