scholarly journals An Exact Solution Approach for the Bus Line Planning Problem with Integrated Passenger Routing

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Evert Vermeir ◽  
Wouter Engelen ◽  
Johan Philips ◽  
Pieter Vansteenwegen
Keyword(s):  
Optimal Solution ◽  
Combinatorial Problem ◽  
Network Design Problem ◽  
Planning Problem ◽  
Optimal Solutions ◽  
Line Planning ◽  
Solution Approach ◽  
Benchmark Instances ◽  
Transit Network Design ◽  
Passenger Routing

The bus line planning problem or transit network design problem with integrated passenger routing is a challenging combinatorial problem. Although well-known benchmark instances for this problem have been available for decades, the state of the art lacks optimal solutions for these instances. The branch and bound algorithm, presented in this paper, introduces three novel concepts to determine these optimal solutions: (1) a new line pool generation method based on dominance, (2) the introduction of essential links, i.e., links which can be determined beforehand and must be present in the optimal solution, and (3) a new network representation based on adding only extra edges. Next to presenting the newly obtained optimal solutions, each of the abovementioned concepts is examined in isolation in the experiments, and it is shown that they contribute significantly to the success of the algorithm.

Pareto Optimal Solution Selection for a Multi-Site Supply Chain Planning Problem Using the VIKOR and TOPSIS Methods

2017 ◽  
Vol 8 (3) ◽  
pp. 21-39 ◽  
Author(s):  
Houssem Felfel ◽  
Omar Ayadi ◽  
Faouzi Masmoudi
Keyword(s):  
Supply Chain ◽  
Optimal Solution ◽  
Quality Level ◽  
Planning Problem ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Compromise Solution ◽  
Optimal Solutions ◽  
Pareto Solution ◽  
Solution Approach

In this paper, a multi-objective, multi-product, multi-period production and transportation planning problem in the context of a multi-site supply chain is proposed. The developed model attempts simultaneously to maximize the profit and to maximize the product quality level. The objective of this paper is to provide the decision maker with a front of Pareto optimal solutions and to help him to select the best Pareto solution. To do so, the epsilon-constraint method is adopted to generate the set of Pareto optimal solutions. Then, the technique for order preference by similarity to ideal solution (TOSIS) is used to choose the best compromise solution. The multi-criteria optimization and compromise solution (VIKOR), a commonly used method in multiple criteria analysis, is applied in order to evaluate the selected solutions using TOPSIS method. This paper offers a numerical example to illustrate the solution approach and to compare the obtained results using TOSIS and VIKOR methods.

scholarly journals Optimum Distribution System Expansion Planning Incorporating DG Based on N-1 Criterion for Sustainable System

2021 ◽  
Vol 13 (12) ◽  
pp. 6708
Author(s):  
Hamza Mubarak ◽  
Nurulafiqah Nadzirah Mansor ◽  
Hazlie Mokhlis ◽  
Mahazani Mohamad ◽  
Hasmaini Mohamad ◽  
...  
Keyword(s):  
Power Systems ◽  
Distribution System ◽  
Industrial Revolution ◽  
Optimal Solution ◽  
Search Space ◽  
Planning Problem ◽  
System Expansion ◽  
Optimum Distribution ◽  
Optimal Sizing ◽  
Expansion Planning

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.

scholarly journals Temporal concatenation for Markov decision processes

2021 ◽  
pp. 1-28
Author(s):  
Ruiyang Song ◽  
Kuang Xu
Keyword(s):  
Markov Decision Processes ◽  
Large Scale ◽  
Optimal Solution ◽  
Upper Bounds ◽  
Black Box ◽  
Decision Processes ◽  
Optimal Solutions ◽  
Wide Range ◽  
Markov Decision ◽  
Speed Up

We propose and analyze a temporal concatenation heuristic for solving large-scale finite-horizon Markov decision processes (MDP), which divides the MDP into smaller sub-problems along the time horizon and generates an overall solution by simply concatenating the optimal solutions from these sub-problems. As a “black box” architecture, temporal concatenation works with a wide range of existing MDP algorithms. Our main results characterize the regret of temporal concatenation compared to the optimal solution. We provide upper bounds for general MDP instances, as well as a family of MDP instances in which the upper bounds are shown to be tight. Together, our results demonstrate temporal concatenation's potential of substantial speed-up at the expense of some performance degradation.

scholarly journals Neutrosophic Number Optimization Models and Their Application in the Practical Production Process

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Angyan Tu ◽  
Jun Ye ◽  
Bing Wang
Keyword(s):  
Production Process ◽  
Optimal Solution ◽  
Optimization Models ◽  
Optimal Solutions ◽  
Practical Applications ◽  
Linear And Nonlinear Programming ◽  
Constrained Conditions ◽  
Minimum Objective Function ◽  
Maximum Minimum ◽  
Neutrosophic Number

In order to simplify the complex calculation and solve the difficult solution problems of neutrosophic number optimization models (NNOMs) in the practical production process, this paper presents two methods to solve NNOMs, where Matlab built-in function “fmincon()” and neutrosophic number operations (NNOs) are used in indeterminate environments. Next, the two methods are applied to linear and nonlinear programming problems with neutrosophic number information to obtain the optimal solution of the maximum/minimum objective function under the constrained conditions of practical productions by neutrosophic number optimization programming (NNOP) examples. Finally, under indeterminate environments, the fit optimal solutions of the examples can also be achieved by using some specified indeterminate scales to fulfill some specified actual requirements. The NNOP methods can obtain the feasible and flexible optimal solutions and indicate the advantage of simple calculations in practical applications.

scholarly journals Realtime production scheduling and control systems in smart industry

Impact ◽  
2020 ◽  
Vol 2020 (8) ◽  
pp. 60-61
Author(s):  
Wei Weng
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Production Scheduling ◽  
Production Control ◽  
Optimal Solution ◽  
Scheduling Problem ◽  
Optimal Solutions ◽  
Scheduling Problems ◽  
Smart Industry ◽  
And Control

For a production system, 'scheduling' aims to find out which machine/worker processes which job at what time to produce the best result for user-set objectives, such as minimising the total cost. Finding the optimal solution to a large scheduling problem, however, is extremely time consuming due to the high complexity. To reduce this time to one instance, Dr Wei Weng, from the Institute of Liberal Arts and Science, Kanazawa University in Japan, is leading research projects on developing online scheduling and control systems that provide near-optimal solutions in real time, even for large production systems. In her system, a large scheduling problem will be solved as distributed small problems and information of jobs and machines is collected online to provide results instantly. This will bring two big changes: 1. Large scheduling problems, for which it tends to take days to reach the optimal solution, will be solved instantly by reaching near-optimal solutions; 2. Rescheduling, which is still difficult to be made in real time by optimization algorithms, will be completed instantly in case some urgent jobs arrive or some scheduled jobs need to be changed or cancelled during production. The projects have great potential in raising efficiency of scheduling and production control in future smart industry and enabling achieving lower costs, higher productivity and better customer service.

Determination of the base position and working area for mobile manipulators

2016 ◽  
Vol 36 (1) ◽  
pp. 80-88 ◽  
Author(s):  
Shunan Ren ◽  
Xiangdong Yang ◽  
Jing Xu ◽  
Guolei Wang ◽  
Ying Xie ◽  
...  
Keyword(s):  
Operation Mode ◽  
Mobile Manipulator ◽  
Planning Problem ◽  
Mobile Manipulators ◽  
Line Planning ◽  
Content Type ◽  
Practical Applications ◽  
Base Position ◽  
Intersection Area ◽  
Intersection Line

Purpose – The purpose of this paper is to determine the base position and the largest working area for mobile manipulators. The base position determines the workspace of the mobile manipulator, particularly when the operation mode is intermittent (i.e. the mobile platform stops when the manipulator conducts the task). When the base of the manipulator is in the intersection area of the Base’s Workable Location Spaces (BWLSes), the end effector (EE) can reach all path points. In this study, the intersection line of BWLSes is calculated numerically, and the largest working area is determined using the BWLS concept. The performance of this method is validated with simulations on specific surface segments, such as plane, cylinder and conical surface segments. Design/methodology/approach – The BWLS is used to determine the largest working area and the base position in which the mobile manipulator can reach all path points with the objective of reducing off-line planning time. Findings – Without considering the orientation of the EE, the base position and the working area for the mobile manipulator are determined using the BWLS. Compared to other methods, the proposed algorithm is beneficial when the planning problem has six dimensions, ensuring the reachability and stability of the EE. Originality/value – The algorithm needs no manual configuration, and its performance is investigated for typical surfaces in practical applications.

NEW IMPROVED METHOD FOR SOLVING THE FUZZY LINEAR PROGRAMMING PROBLEMS WITH VARIABLES GIVEN AS FUZZY NUMBERS

2021 ◽  
Vol 10 (12) ◽  
pp. 3699-3723
Author(s):  
L. Kané ◽  
M. Konaté ◽  
L. Diabaté ◽  
M. Diakité ◽  
H. Bado
Keyword(s):  
Linear Programming ◽  
Fuzzy Numbers ◽  
Optimal Solution ◽  
Fuzzy Linear Programming ◽  
Interval Linear Programming ◽  
Interval Numbers ◽  
Programming Technique ◽  
Solution Approach ◽  
Interval Linear ◽  
Linear Programming Problems

The present paper aims to propose an alternative solution approach in obtaining the fuzzy optimal solution to a fuzzy linear programming problem with variables given as fuzzy numbers with minimum uncertainty. In this paper, the fuzzy linear programming problems with variables given as fuzzy numbers is transformed into equivalent interval linear programming problems with variables given as interval numbers. The solutions to these interval linear programming problems with variables given as interval numbers are then obtained with the help of linear programming technique. A set of six random numerical examples has been solved using the proposed approach.

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