METODOLOGIJA I ALGORITAM ZA OPTIMIZACIJU LANCA PROCESA TRANSPORTA ASFALTA

In this paper authors suggest and test evolutionary algorithm of multiple criteria solver (MCS) for asphalt supply chain optimization. On the basis of the defined imperfection of the basic mathematical model authors made an algorithm and conducted simulations of transportation problems cases generated from the given realistic input intervals in order to determine the constraints and possibilities for improvement of the original model of the transportation problem of large amounts of asphalt mixture. Results have shown that the suggested model verifies and eliminates the lack of the original model. As well, it is shown in which scenarios of transportation problem and to which extent the suggested methodology contributes to the total transportation costs savings and insurance of the program’s optimality.U radu je predložen i testiran evolucijski algoritam za optimizaciju lanca procesa transporta asfaltne mješavine na gradilišta. Izrađen je algoritam (rješavatelj MCS) na temelju definiranog nedostatka postojećeg matematičkog modela te provedena simulacija slučajeva transportnog problema kako bi se utvrdila ograničenja i mogućnosti za poboljšanje originalnog modela za rješavanje transportnog problema velikih količina asfaltne mješavine. Rezultati su pokazali da predložen model pridruživanja i isključivanja potencijalnih izvora potvrđuje i otklanja nedostatak originalnog modela. Pokazano je i u kojim slučajevima transportnog problema i u kojoj mjeri predložena metodologija doprinosi uštedi i osiguranju optimalnosti ponuđenog programa

A Decomposition Algorithm for Single and Multiobjective Integrated Market Selection and Production Planning

We study an integrated market selection and production planning problem. There is a set of markets with deterministic demand, and each market has a certain revenue that is obtained if the market's demand is satisfied throughout a planning horizon. The demand is satisfied with a production scheme that has a lot-sizing structure. The problem is to decide on which markets' demand to satisfy and plan the production simultaneously. We consider both single and multiobjective settings. The single objective problem maximizes the profit, whereas the multiobjective problem includes the maximization of the revenue and the minimization of the production cost objectives. We develop a decomposition-based exact solution algorithm for the single objective setting and show how it can be used in a proposed three-phase algorithm for the multiobjective setting. The master problem chooses a subset of markets, and the subproblem calculates an optimal production plan to satisfy the selected markets' demand. We investigate the subproblem from a cooperative game theory perspective to devise cuts and strengthen them based on lifting. We also propose a set of valid inequalities and preprocessing rules to improve the proposed algorithm. We test the efficacy of our solution method over a suite of problem instances and show that our algorithm substantially decreases solution times for all problem instances.</p