This paper deals with minimization of tardiness in single machine scheduling problem when each job has two different due-dates i.e. ordinary due-date and drop dead date. The drop dead date is the date in which jobs’ weights rise sharply or the customer cancels the order. A linear programming formulation is developed for the problem and since the problem is known to be NP-hard, three heuristic...

Even though people are capable of making decisions in a thorough and methodical way, it appears that most of the time they don’t. A growing body of research suggests that people unconsciously use simple rules of thumb, or heuristics, to navigate the routine complexities of modern life. In this paper, I examine evidence that four of these heuristics – familiarity, social proof, commitment and sc...

this paper considers the economic lot scheduling problem, that is, the problem of scheduling several products on a single facility so as to minimize holding and setup costs. combination of frequency and timing as well as production quantity make this problem np-hard. a heuristic is developed to obtain a good solution to elsp. the proposed heuristic makes use of the simulated annealing technique...

Ant Colony Optimization (ACO) is a kind of randomized search heuristic that has become very popular for solving problems from combinatorial optimization. Solutions for a given problem are constructed by a random walk on a so-called construction graph. This random walk can be influenced by heuristic information about the problem. In contrast to many successful applications, the theoretical found...

Leveraging the benefits of business intelligence and analytics (BI&A) and improving decision quality does not only depend on establishing BI&A technology, but also on the organization and characteristics of decision processes. This research investigates new perspectives on these decision processes and establishes a link between characteristics of BI&A support and decision makers’ modes of infor...

Flow shop sequencing problem is included in NP-hard problems and a number of heuristic methods have been developed to solve it. Most of these methods are offered for the crisp processing time. However fuzzy algorithm is appropriate for the problems with fuzzy processing time. This paper presents a method in which an algorithm is used to minimize make span of flow shop with fuzzy processing time...

This paper describes a challenging plan recognition problem that arises in environments in which agents engage widely in exploratory behavior, and presents new algorithms for effective plan recognition in such settings. In exploratory domains, agents’ actions map onto logs of behavior that include switching between activities, extraneous actions, and mistakes. Flexible pedagogical software, suc...

Generic Iterative Simulated-Annealing Search (GISS) is a hyper-heuristic algorithm inspired on a Simulated Annealing driven method, on this context its used to explore across the different instance-heuristicstate search space. On this extended abstract we describe the proposed approach, characteristics and others technicals parameters.

Heuristic techniques are optimization methods that inspired by nature. Although there many heuristics in the literature, a new heuristic technique is presented researchers every day observing nature-based or living behaviors In this study, human behavior proposed. order to prove validity of method called Search and Rescue Optimization Algorithm (AKOA), applied find global minimums function test...

Swarm Intelligent Systems are computational models of the spatial evolution of populations explaining it as a global behavior emerging from locally controlled movements, which are guided by decisions taken on the basis of local information. The increase of agents’ cognitive capabilities, endowing them with memory and with the ability of selecting the rules of movement depending on an internal s...