Abstract: In this paper, a mixed integer linear programming (MILP) model is presented to solve the flexible job shop scheduling problem (FJSP). This problem is one of the hardest combinatorial problems. The objective considered is the minimization of the makespan. The computational results of the proposed MILP model were compared with those of the best known mathematical model in the literature in terms of the computational time. The results show that our model has better performance with respect to all the considered performance measures including relative percentage deviation (RPD) value, number of constraints, and total number of variables. By this improved mathematical model, larger FJS problems can be optimally solved in reasonable time, and therefore, the model would be a better tool for the performance evaluation of the approximation algorithms developed for the problem.
Abstract: This paper presents the development of an electricity simulation model taking into account electrical network constraints, applied on the Belgian power system. The base of the model is optimizing an extensive Unit Commitment (UC) problem through the use of Mixed Integer Linear Programming (MILP). Electrical constraints are incorporated through the implementation of a DC load flow. The model encloses the Belgian power system in a 220 – 380 kV high voltage network (i.e., 93 power plants and 106 nodes). The model features the use of pumping storage facilities as well as the inclusion of spinning reserves in a single optimization process. Solution times of the model stay below reasonable values.
Abstract: Rapid economic development and population growth
in Malaysia had accelerated the generation of solid waste. This issue
gives pressure for effective management of municipal solid waste
(MSW) to take place in Malaysia due to the increased cost of landfill.
This paper discusses optimal planning of waste-to-energy (WTE)
using a combinatorial simulation and optimization model through
mixed integer linear programming (MILP) approach. The proposed
multi-period model is tested in Iskandar Malaysia (IM) as case study
for a period of 12 years (2011 -2025) to illustrate the economic
potential and tradeoffs involved in this study. In this paper, 3
scenarios have been used to demonstrate the applicability of the
model: (1) Incineration scenario (2) Landfill scenario (3) Optimal
scenario. The model revealed that the minimum cost of electricity
generation from 9,995,855 tonnes of MSW is estimated as USD
387million with a total electricity generation of 50MW /yr in the
optimal scenario.