From a practical point of view, most problems cannot be optimally solved applying brute-force single-agent search algorithms. Thus, a new class of single-agent search algorithms was devised to find the optimal solution faster and/or consuming less space, heuristic single-agent search algorithms. However, designing accurate heuristic functions is still a major challenge. In this paper, a mathema...

Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs.  In this paper, just-in-time (JIT) flow shop scheduling problem with preemp...

Proper arrangement of facility layout is a key issue in management that influences efficiency and the profitability of the manufacturing systems. Parallel Row Ordering Problem (PROP) is a special case of facility layout problem and consists of looking for the best location of n facilities while similar facilities (facilities which has some characteristics in common) should be arranged in a row ...

The Vehicle Routing Problem (VRP), a famous problem of operation research, holds a central place in combinatorial optimization problems. In this problem, a fleet vehicles with Q capacity start to move from depot and return after servicing to customers in which visit only ones each customer and load more than its capacity not at all. The objective is to minimize the number of used vehicles and t...

Heuristic search is a central component of many important applications in AI including automated planning. While we can find optimal solutions to heuristic search problems, doing so may take hours or days. For practical applications, this is unacceptably slow, and we must rely on algorithms which find solutions of high, but not optimal, quality or ones which bound the time used directly. In my ...

This paper proposes two variants of heuristic algorithms to solve the classic permutation flowshop scheduling problem. Both algorithms are simple and very efficient. The first algorithm is a constructive heuristic which builds the optimal schedule of jobs on the basis of a selective-greedy process. To escape the trap of local optimum points, for the second heuristic algorithm a stochastic featu...

production planning and scheduling are the most important issues of the production industries, which have a considerable influence on the productivity of the production systems. although, production planning and scheduling are in two different medium-term and short-term decision making levels, there are a very close relationship between them. ignoring this important feature in production planni...

We present a local improvement heuristic for genetic algorithms, and term it a Kernighan-Lin style heuristic. We analyze the runtime cost of the heuristic, and show that it can be affordable. We then demonstrate through experiments that the heuristic provides very quick solutions to several problems which have been touted in the literature as especially hard ones for genetic algorithms. We sugg...

Heuristic search using algorithms such as A and IDA is the prevalent method for obtaining optimal sequential solutions for classical planning tasks. Theoretical analyses of these classical search algorithms, such as the well-known results of Pohl, Gaschnig and Pearl, suggest that such heuristic search algorithms can obtain better than exponential scaling behaviour, provided that the heuristics ...

In this paper, the problem of determining the best schedule for a set of projects has been modeled in the form of a generalized tardiness flowshop (GTF) problem. We develop a set of heuristic algorithms for minimizing the total tardiness of jobs in a GTF problem. In the generalized version of tardiness flowshop problems, a job is considered to be a collection of operations and there is a due da...