scholarly journals NUMERICAL SOLUTION TECHNIQUE FOR JOINT CHANCE-CONSTRAINED PROGRAMMING PROBLEM : AN APPLICATION TO ELECTRIC POWER CAPACITY EXPANSION

1999 ◽  
Vol 42 (2) ◽  
pp. 128-140 ◽  
Author(s):  
Takayuki Shiina
Keyword(s):  
Numerical Solution ◽  
Electric Power ◽  
Programming Problem ◽  
Capacity Expansion ◽  
Solution Technique ◽  
Chance Constrained Programming ◽  
Power Capacity ◽  
Constrained Programming

A Chance Constrained Programming Approach to the Integrated Planning of Electric Power Generation, Natural Gas Network and Storage

2018 ◽  
Vol 33 (6) ◽  
pp. 6883-6893 ◽  
Author(s):  
Babatunde Odetayo ◽  
Mostafa Kazemi ◽  
John MacCormack ◽  
William D. Rosehart ◽  
Hamidreza Zareipour ◽  
...  
Keyword(s):  
Power Generation ◽  
Natural Gas ◽  
Electric Power ◽  
Programming Approach ◽  
Chance Constrained Programming ◽  
Integrated Planning ◽  
Gas Network ◽  
Natural Gas Network ◽  
Constrained Programming ◽  
And Storage

scholarly journals A Novel Method for Optimal Solution of Fuzzy Chance Constraint Single-Period Inventory Model

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Anuradha Sahoo ◽  
J. K. Dash
Keyword(s):  
Programming Problem ◽  
Fuzzy Random Variable ◽  
Optimal Solution ◽  
Random Variable ◽  
Chance Constraint ◽  
Chance Constrained Programming ◽  
Storage Space ◽  
Weighted Sum Method ◽  
Single Period ◽  
Constrained Programming

A method is proposed for solving single-period inventory fuzzy probabilistic model (SPIFPM) with fuzzy demand and fuzzy storage space under a chance constraint. Our objective is to maximize the total profit for both overstock and understock situations, where the demandD~jfor each productjin the objective function is considered as a fuzzy random variable (FRV) and with the available storage space areaW~, which is also a FRV under normal distribution and exponential distribution. Initially we used the weighted sum method to consider both overstock and understock situations. Then the fuzziness of the model is removed by ranking function method and the randomness of the model is removed by chance constrained programming problem, which is a deterministic nonlinear programming problem (NLPP) model. Finally this NLPP is solved by using LINGO software. To validate and to demonstrate the results of the proposed model, numerical examples are given.

scholarly journals Solution to Chance Constrained Programming Problem in Swap Trailer Transport Organisation based on Improved Simulated Annealing Algorithm

2020 ◽  
Vol 5 (1) ◽  
pp. 47-54 ◽  
Author(s):  
Tao Li ◽  
Wenyin Yang
Keyword(s):  
Simulated Annealing ◽  
Programming Problem ◽  
Vehicle Routing Problem ◽  
Simulated Annealing Algorithm ◽  
Chance Constrained Programming ◽  
Routing Problem ◽  
Theoretical Support ◽  
Annealing Algorithm ◽  
Constrained Programming

AbstractSwap trailer transport organisation problem originates from the traditional vehicle routing problem (VRP). Most of the studies on the problems assume that the travelling times of vehicles are fixed values. In this paper, the uncertainties of driving times are considered and a chance constrained programming problem is proposed. An improved simulated annealing algorithm is used to solve the problem proposed. The model and algorithm described in this paper are studied through a case study, and the influence of uncertainty on the results is analysed. The conclusion of this study provides theoretical support for the practice of trailer pickup transport.

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