1. Assignment problems in logisticsJanez Povh, 2008, izvirni znanstveni članek Opis: We consider two classical problems from location theory which may serve as theoretical models for several logistic problems where one wants to assign elements of a set A to elements of a set B such that some linear or quadratic function attains its minimum. It turns out that linear objective function yields a linear assignment problem, which can be solved easily by several primaldual methods like Hungarian method, Shortest augmenting path method etc. On the other hand, taking quadratic objective function into account makes the problem much harder. The resulting quadratic assignment problem is a very useful model but also very tough problem from theoretical and practical point of view. We list several wellknown applications of these models and also the most effective methods to solve the problem. However, it is still a challenging task to solve this problem to optimality when the size of underlying sets A and B is greater than 25 and currently impossible task when the size is greater than 35. Ključne besede: quadratic assignment problem, linear assignment problem, branch and bound algorithm, heuristics Objavljeno: 05.06.2012; Ogledov: 898; Prenosov: 57 Celotno besedilo (204,96 KB) Gradivo ima več datotek! Več...

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3. Heuristic approach to inventory control with advance capacity informationMarko Jakšič, Borut Rusjan, 2009, izvirni znanstveni članek Opis: There is a growing trend of information sharing within modern supply chains. This trend is mainly stimulated by recent developments in information technology and the increasing awareness that accurate and timely information helps firms cope with volatile and uncertain business conditions. We model a periodicreview, singleitem, capacitated stochastic inventory system, where a supply chain member has the ability to obtain advance capacity information (‘ACI’) about future supply capacity availability. ACI is used to reduce the uncertainty of future supply and thus enables the decisionmaker to make better ordering decisions. We develop an easily applicable heuristic based on insights gained from an analysis of the optimal policy. In a numerical study we quantify the benefits of ACI and compare the performance of the proposed heuristic with the optimal performance. We illustrate the conditions in which the procedure is working well and comment on its practical applicability. Ključne besede: inventories, supply, stochastic processes, operations research, heuristics Objavljeno: 30.11.2017; Ogledov: 236; Prenosov: 149 Celotno besedilo (1,02 MB) Gradivo ima več datotek! Več...

4. Multiobjective optimization algorithms with the island metaheuristic for effective project management problem solvingChristina Brester, Ivan Ryzhikov, Eugene Semenkin, 2017, izvirni znanstveni članek Opis: Background and Purpose: In every organization, project management raises many different decisionmaking problems, a large proportion of which can be efficiently solved using specific decisionmaking support systems. Yet such kinds of problems are always a challenge since there is no timeefficient or computationally efficient algorithm to solve them as a result of their complexity. In this study, we consider the problem of optimal financial investment. In our solution, we take into account the following organizational resource and project characteristics: profits, costs and risks.
Design/Methodology/Approach: The decisionmaking problem is reduced to a multicriteria 01 knapsack problem. This implies that we need to find a nondominated set of alternative solutions, which are a tradeoff between maximizing incomes and minimizing risks. At the same time, alternatives must satisfy constraints. This leads to a constrained twocriterion optimization problem in the Boolean space. To cope with the peculiarities and high complexity of the problem, evolutionbased algorithms with an island metaheuristic are applied as an alternative to conventional techniques.
Results: The problem in hand was reduced to a twocriterion unconstrained extreme problem and solved with different evolutionbased multiobjective optimization heuristics. Next, we applied a proposed metaheuristic combining the particular algorithms and causing their interaction in a cooperative and collaborative way. The obtained results showed that the island heuristic outperformed the original ones based on the values of a specific metric, thus showing the representativeness of Pareto front approximations. Having more representative approximations, decisionmakers have more alternative project portfolios corresponding to different risk and profit estimations. Since these criteria are conflicting, when choosing an alternative with an estimated high profit, decisionmakers follow a strategy with an estimated high risk and vice versa.
Conclusion: In the present paper, the project portfolio decisionmaking problem was reduced to a 01 knapsack constrained multiobjective optimization problem. The algorithm investigation confirms that the use of the island metaheuristic significantly improves the performance of genetic algorithms, thereby providing an efficient tool for Financial Responsibility Centres Management. Ključne besede: 01 multiobjective constrained knapsack problem, project management portfolio problem, multiobjective evolutionbased optimization algorithms, collaborative and cooperative metaheuristics Objavljeno: 04.05.2018; Ogledov: 437; Prenosov: 137 Celotno besedilo (993,98 KB) Gradivo ima več datotek! Več...
