Fungal endophytes are microorganisms living symbiotically with a host plant. They can produce volatile organic compounds (VOCs) that have antimicrobial activity. This study aimed to isolate endophytic fungi from Barleria prionitis plants grown in Thailand and to investigate the antifungal properties of their VOCs against Colletotrichum acutatum, a causal agent of anthracnose disease on post-harvest strawberry fruits. A total of 34 endophytic fungi were isolated from leaves of B. prionitis. The VOCs produced from each individual isolate were screened for their antifungal activity against C. acutatum using a dual-culture plate method. From this in vitro screening experiment, the VOCs produced by the endophytic isolate BP11 were found to have the highest inhibition percentage (80.3%) against the mycelial growth of C. acutatum. The endophytic isolate BP11 was molecularly identified as Daldinia eschscholtzii MFLUCC 19-0493. This strain was then selected for an in vivo experiment. Results from the in vivo experiment indicated that the VOCs produced by D. eschscholtzii MFLUCC 19-0493 were able to inhibit infections by C. acutatum on organic fresh strawberry fruits with an average inhibition percentage of 72.4%. The quality of the pathogen-inoculated strawberry fruits treated with VOCs produced by D. eschscholtzii MFLUCC 19-0493 was evaluated. Their fruit firmness, total soluble solids, and pH were found to be similar to the untreated strawberry fruits. Solid phase microextraction-gas chromatographic-mass spectrometric analysis of the VOCs produced by D. eschscholtzii MFLUCC 19-0493 led to the detection and identification of 60 compounds. The major compounds were elemicin (23.8%), benzaldehyde dimethyl acetal (8.5%), ethyl sorbate (6.8%), methyl geranate (6.5%), trans-sabinene hydrate (5.4%), and 3,5-dimethyl-4-heptanone (5.1%). Each major compound was tested for its antifungal activity against C. acutatum using the in vitro assay. While all these selected VOCs showed varying degrees of antifungal activity, elemicin was found to possess the strongest antifungal activity. This work suggests that D. eschscholtzii MFLUCC 19-0493 could be a promising natural preservative for controlling C. acutatum associated anthracnose disease in strawberry fruits during the post-harvest period.

We address a variant of the unbounded knapsack problem (UKP) into which the processing time of each item is also put and considered, referred as MMPTUKP. The MMPTUKP is a decision problem of allocating amount of n items, such that the maximum processing time of the selected items is minimized and the total profit is gained as at least as determined without exceeding capacity of knapsack. In this study, we proposed a new exact algorithm for this problem, called MMPTUKP algorithm. This pseudo polynomial time algorithm solves the bounded knapsack problem (BKP) sequentially with the updated bounds until reaching an optimal solution. We present computational experience with various data instances randomly generated to validate our ideas and demonstrate the efficiency of the proposed algorithm

Generally, transportation costs account for approximately half of the total operation expenses of a logistics firm. Therefore, any effort to optimize the planning of vehicle routing would be substantially beneficial to the company. This study focuses on a postman delivery routing problem of the Chiang Rai post office, located in the Chiang Rai province of Thailand. In this study, two metaheuristic methods—particle swarm optimization (PSO) and differential evolution (DE)—were applied with particular solution representation to find delivery routings with minimum travel distances. The performances of PSO and DE were compared along with those from current practices. The results showed that PSO and DE clearly outperformed the actual routing of the current practices in all the operational days examined. Moreover, DE performances were notably superior to those of PSO.

Transportation costs account for a large portion of business expense in any logistics firm; thus, achieving proper solutions that manage those transportation activities well and reduce such expense should be the number one priority for the business. Essentially, such logistics management involves the routing plans for company vehicles that perform delivery/pick up and also the number of vehicles utilized. This study investigated and compared the optimization performances of routing algorithms using simulated geographic data based in Chiang Rai, Thailand, emulating the post office operation which had 1 post office, 4 delivery vehicles and 2 delivery zones (2 vehicles per zone): 65 customer locations for zone A and 74 for zone B. The major objective of this particular routing problem, called Vehicle Routing Problem (VRP), was that the total delivery distance of those 4 delivery vehicles combined should be minimized; moreover, those vehicles mush finish their delivery operation within a time constraint, set at 2 hours. The optimization algorithms, employed for the routing procedures, were Large Neighborhood Search (LNS), Particle Swarm Optimization (PSO), Differential Evolution (DE) and Ant Colony Optimization (ACO), combined into 3 hybrid algorithms (LNS|PSO, LNS|DE and LNS|ACO). Those hybrid algorithms including pure ones (DE, PSO and ACO) were compared for their optimization performances; and the results showed that LNS|ACO hybrid algorithm was superior than the other two hybrid ones and also far better than pure DE, PSO and ACO algorithms at various parameter variants. Additionally, most algorithms (hybrid and pure ones) finished the delivery routing within the time constraint of 2 hours except only for the pure algorithms at minimum parameter variant.