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The transportation problem has been widely studied in the field of supply chain management where circulation of products with a minimal transportation cost is an important issue. This paper presents the first adaptation of the Dhouib-Matrix-TP1 heuristic to solve the transportation problem in single-valued trapezoidal neutrosophic environment. Hence, the recently developed Dhouib-Matrix-TP1 heuristic is enriched with two functions to solve the neutrosophic transportation problem. On the one hand, a defuzzification function is exploited in order to convert the single-valued trapezoidal neutrosophic numbers to crisp numbers. On the other hand, an original metric function (Average-Min) is proposed with the intention of performing the nodes selection process. With an illustration from a literature example, we show to the decision maker the multiple advantages of the novel heuristic Dhouib-Matrix-TP1 which can be easily implemented in real-life industrial transportation under neutrosophic environment.

SUMMARYA multi-start threshold accepting algorithm with an adaptive memory (MS-TA) is proposed to solve multiple objective continuous optimization problems. The aim of this paper is to find efficiently multiple Pareto-optimal solutions. Comparisons are carried out with multiple objective taboo search algorithm and genetic algorithm. Experiments on literature problems show that the proposed algorithm is more effective. The presented multi-start adaptive algorithm improves the best-known results by a significant margin.

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