A hybrid particulate swarm optimization (hybrid) combination of an algorithm the particle and a variable neighborhood search is proposed for multi-objective permutation flow shop scheduling problem (PFSP) with smallest cumulative completion time total time. Algorithm (HPSO) applied to maintain fair centralized decentralized search. The Nawaz-Enscore-Ham )NEH) heuristic in this used initialize p...

This paper proposes a multi-objective bidding strategy for a generation company (GenCo) in a day-ahead uniform price spot market using non-dominated sorting particle swarm optimisation (NSPSO). NSPSO is introduced to solve the multi-objective strategic bidding problem considering expected profit maximisation and risk (profit variation) minimisation. Monte Carlo (MC) simulation is employed to si...

This work presents three multi-objective heuristic algorithms based on Two-phase Pareto Local Search with VNS (2PPLS-VNS), Multi-objective Variable Neighborhood Search (MOVNS) and Non-dominated Sorting Genetic Algorithm II (NSGA-II). The algorithms were applied to the open-pit-mining operational planning problem with dynamic truck allocation (OPMOP). Approximations to Pareto sets generated by t...

In this study the performance and emissions characteristics of a heavy-duty, direct injection, Compression ignition (CI) engine which is specialized in agriculture, have been investigated experimentally. For this aim, the influence of injection timing, load, engine speed on power, brake specific fuel consumption (BSFC), peak pressure (PP), nitrogen oxides (NOx), carbon dioxide (CO2), Carbon mon...

This paper introduces a Travel Demand Management (TDM) model in order to decrease the transportation externalities by affecting on passengers’travel choices. Thus, a bi-objective bi-modal optimization model for road pricing is developed aiming to enhance environmental and social sustainability by considering to minimize the air pollution and maximize the social welfare as its objectives. This m...