In single-objective optimization it is possible to find a global optimum, while in the multi-objective case no optimal solution is clearly defined, but several that simultaneously optimize all the objectives. However, the majority of this kind of problems cannot be solved exactly as they have very large and highly complex search spaces. Recently, meta-heuristic approaches have become important ...

In textile industry, marker planning is one of the main operations in the cutting fabric stage. Marker packing is usually used to maximize cloth exploitation and minimize its waste. In this research, a method is used based on new found meta-heuristic imperialist competitive algorithm (ICA) and Bottom-Left-Fill Algorithm (BLF) to achieve optimal marker packing. Function of the proposed method wa...

Assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. In this study, we solve quadratic assignment problem (QAP), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. It should be noted that any facility must be assign to only one location. In this paper, first o...

barrel vaults are attractive space structures that cover large area without intermediate supports. in this paper, the charged search system (css) optimization algorithm is employed for optimal design of barrel vaults. this method utilizes the governing laws of coulomb and gauss from electrostatics and the newtonian law of mechanics. the results demonstrate the efficiency of the discrete css alg...

This paper presents a new multi objective heuristic algorithm for Dynamic Economic Load Dispatch (DELD) problem soultion with transmission losses based on new version of the Particle Swarm Optimization (PSO) algorithm, which called Multi Objective PSO (MOPSO) method. The proposed algorithm is based on multi objective meta-heuristics technique that evaluates a set of the Pareto solutions systema...

We present several heuristic algorithms based on tabu search for solving the multi-stage sequence-dependent group scheduling (SDGS) problem by considering minimization of makespan as the criterion. As the problem is recognized to be strongly NP-hard, several meta (tabu) search-based solution algorithms are developed to efficiently solve industry-size problem instances. Also, two different initi...

this paper investigates the problem of just-in-time permutation flow shop scheduling with limited buffers and linear job deterioration in an uncertain environment. the fuzzy set theory is applied to describe this situation. a novel mixed-integer nonlinear program is presented to minimize the weighted sum of fuzzy earliness and tardiness penalties. due to the computational complexities, the prop...